Depression is a common mental disorder that falls under the category of "stagnation syndrome" in traditional Chinese medicine （TCM）. Its complex pathogenesis poses challenges for the development of novel therapeutic agents. Currently， clinically used antidepressants are often accompanied by significant side effects， and statistics show that about one-third of patients do not respond to these medications. TCM demonstrates advantages in the treatment of depression through multi-target， multi-pathway and multi-mechanistic approaches. Pinelliae Rhizoma， a phlegm-resolving herb， exhibits effects such as drying dampness and resolving phlegm， as well as eliminating stuffiness and reducing masses. The characteristics of harmonizing Yin and Yang and resolving stagnation in the middle energizer align precisely with the pathogenesis of depression syndrome， demonstrating therapeutic efficacy in affected patients. Literature studies have found that the active ingredients of Pinelliae Rhizoma， such as cavidine， baicalein， β-sitosterol， as well as Pinelliae Rhizoma herb pairs， such as Pinelliae Rhizoma-Magnoliae Officinalis Cortex， Pinelliae Rhizoma-husked sorghum， Pinelliae Rhizoma-Prunellae Spica， exhibit significant antidepressant effects. Furthermore， TCM formulas containing Pinelliae Rhizoma as the principal therapeutic agent， such as Banxia Xiexin Tang， Banxia Houpo Tang， and Wendan Tang， as well as formulas incorporating Pinelliae Rhizoma like compound Xiaochaihu Tang， Chaihu Jia Longgu Muli Tang， and Erchen Tang， have also demonstrated favorable antidepressant efficacy. The antidepressant mechanism of these agents may involve modulation of 5-hydroxytryptamine （5-HT） and dopamine （DA） levels， up-regulation of brain-derived neurotrophic factor （BDNF） expression， regulation of the hypothalamus-pituitary-adrenal （HPA） axis， reduction of oxidative stress， modulation of nuclear transcription factor-κB （NF-κB） signaling pathway， and inhibition of microglia-mediated inflammatory responses. This review summarized the antidepressant mechanisms and clinical applications of the active components， herb pairs， and TCM formulas containing Pinelliae Rhizoma， aiming to provide a reference for modern research on the use of Pinelliae Rhizoma in antidepressant therapy.

OBJECTIVE To investigate the effect and mechanism of modified Lichong decoction （MLCD） on the apoptosis of transplanted tumor cells in nude mice. METHODS Human gastric cancer AGS cells were cultured， and a nude mice transplanted tumor model was established. The nude mice were divided into the model group and MLCD low-， medium- and high-dose groups （150， 300， 600 mg/kg）. They were given distilled water or the corresponding drug solution by gavage once daily for four consecutive weeks. The size of transplanted tumors in nude mice was measured every six days， and the tumor volume was calculated. After the medication， the nude mice were sacrificed， and the transplanted tumor tissues were isolated. The contents of lactate dehydrogenase （LDH） and reactive oxygen species （ROS） in the transplanted tumor tissues were detected， and the changes in mitochondrial membrane potential were assessed. The pathological morphological changes were observed. The enzymatic activities of caspase-3， caspase-8， and caspase-9， as well as protein expressions of Fas and FasL and mRNA expressions of caspase-3， caspase-8， caspase-9， Fas and FasL in the transplanted tumor tissues， were detected. RESULTS Compared with the model group， the volume of transplanted tumors in nude mice from all MLCD dose groups was reduced to varying degrees. The contents of LDH and ROS， as well as the enzymatic activities of caspase-3， caspase-8 and caspase-9， were significantly increased/enhanced. The mitochondrial membrane potential was significantly decreased. The protein expressions of Fas and FasL， and the mRNA expressions of caspase-3， caspase-8， caspase-9， Fas and FasL were significantly up-regulated. Most of these differences were statistically significant （ P ＜0.05 or P ＜0.01）. Pathological results showed that with increasing doses of MLCD， the cellular density in the transplanted tumor tissues gradually decreased， and typical morphological features of apoptosis， such as loosening and increasing fragmentation， became more prominent. CONCLUSIONS MLCD can induce apoptosis in transplanted tumor cells of nude mice， and its mechanism may be related to the activation of the Fas/FasL pathway and the caspase apoptotic pathway.

ObjectiveTo observe the effects of Danggui Shaoyaosan on macrophage polarization and renal inflammation in db/db mice with diabetic kidney disease （DKD）， and to explore its renal protective effects and underlying mechanisms. MethodsEight db/m mice were assigned to the normal group， and forty db/db mice were randomly divided into a model group， low-， medium-， and high-dose Danggui Shaoyaosan groups （8.39， 16.77， 33.54 g·kg^-1）， and an irbesartan group （0.025 g·kg^-1）. All mice were administered treatment by gavage for 12 consecutive weeks. General conditions of the mice were observed during the intervention. At the end of the 12-week intervention， 24-h urine samples were collected using metabolic cages， after which the mice were anesthetized for sample collection. Blood was collected by enucleation and centrifuged to obtain serum for the determination of glycated serum protein （GSP）， serum creatinine （SCr）， blood urea nitrogen （BUN）， total cholesterol （TC）， and triglycerides （TG）. The urinary albumin-to-creatinine ratio （UACR） was measured. Renal pathological changes were observed using hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum tumor necrosis factor-α （TNF-α）， interleukin-10 （IL-10）， and monocyte chemoattractant protein-1 （MCP-1） levels. Immunofluorescence （IF） was performed to detect F4/80 expression in renal tissue， and immunohistochemistry （IHC） was used to assess CD206 expression. Real-time quantitative polymerase chain reaction （Real-time PCR） was employed to measure the mRNA expression of TNF-α， IL-10， inducible nitric oxide synthase （iNOS）， and arginase-1 （Arg-1）. Western blot analysis was used to detect the protein expression of iNOS， Arg-1， CD86， and CD206 in renal tissue. ResultsCompared with the normal group， the model group showed increased levels of GSP， UACR， SCr， BUN， TC， and TG， elevated levels of the inflammatory factor TNF-α and the chemokine MCP-1， and decreased IL-10 levels （P<0.01）. Pathological examination revealed glomerular hypertrophy， mesangial cell proliferation with marked mesangial expansion， inflammatory cell infiltration， vacuolar degeneration of renal tubular epithelial cells， prominent glycogen deposition， and increased collagen fiber deposition. In addition， relative F4/80 fluorescence intensity was enhanced， CD206 expression in the glomeruli and renal interstitium was reduced， and TNF-α and iNOS mRNA expression was increased. IL-10 and Arg-1 mRNA expression was decreased， iNOS and CD86 protein expression was increased， and Arg-1 and CD206 protein expression was decreased （P<0.05， P<0.01）. Compared with the model group， the Danggui Shaoyaosan groups and the irbesartan group showed decreased levels of GSP， UACR， SCr， BUN， TC， and TG， reduced serum TNF-α and MCP-1 levels， and increased IL-10 levels. Renal pathological damage was improved to varying degrees. Relative F4/80 fluorescence intensity was reduced， CD206 expression in the glomeruli and renal interstitium was increased， and TNF-α and iNOS mRNA expression was decreased. IL-10 and Arg-1 mRNA expression was increased， iNOS and CD86 protein expression was reduced， and Arg-1 and CD206 protein expression was increased （P<0.05， P<0.01）. ConclusionDanggui Shaoyaosan can improve renal function and alleviate renal pathological damage in db/db mice. Its mechanism may be related to inhibiting M1 pro-inflammatory macrophage polarization， promoting M2 anti-inflammatory macrophage polarization， reducing inflammatory responses， delaying the progression of renal fibrosis， improving renal pathological injury， and thereby exerting renal protective effects.

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.

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.

Autosomal dominant polycystic kidney disease （ADPKD） is a systemic hereditary renal disorder and can affect multiple organs， and congenital hepatic fibrosis is one of the manifestations of liver involvement and is an important complication of ADPKD. Symptomatic management is currently the main treatment method for this disease， and disease-specific drugs such as tolvaptan have limited indications and cannot correct the underlying genetic defect. This article reports a case of ADPKD with congenital hepatic fibrosis， and sirolimus was identified as the individualized treatment regimen based on peripheral blood functional genomic analysis and drug sensitivity prediction platform. The patient achieved significant improvements in symptoms and quality of life after treatment， with a stable kidney volume. This case shows that functional genomics has a potential value in guiding individualized treatment of rare genetic disorders， which provides new treatment ideas and practice paths for similar patients.

Background: Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials. Microbial agents, as environmentally friendly and efficient plant growth promoters and soil conditioners, have increasingly attracted attention in eco-agriculture research. Objective: Our understanding remains limited regarding how the application of microbial agents, alone or in combination, affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials. Methods: In this study, Epimedium pubescens Maxim. was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis) applied individually and in combination on plant growth and the accumulation of bioactive components. Additionally, this study explored the relationship between the rhizosphere microbiome and plant development. Results: The application of microbial agents increased the yield of E. pubescens leaves by 20.30% to 33.66% and enhanced the total flavonol glycosides content by 11.40% to 29.94%. Meanwhile, microbial treatments reshaped the rhizosphere microbiome, promoted the enrichment of beneficial microorganisms (e.g., Frankia and Paenibacillus), suppressed phytopathogenic fungi such as Didymella and Scytalidium, and enhanced the stability of the soil microbial co-occurrence network. The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumulation of bioactive components by modulating the soil microbiome. Conclusion: These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere microbiomes as mediated by microbial agents. They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

Objective:To investigate the prognostic value and safety of thoracic radiotherapy in patients with synchronous oligometastatic, driver gene-negative non-small cell lung cancer (NSCLC) receiving immune checkpoint inhibitors (ICIs) as first-line treatment.Methods:Data were retrospectively collected from 55 patients diagnosed with synchronous oligometastatic, driver gene-negative NSCLC who received first-line ICIs from January 2017 to March 2022. These patients were categorized into two groups based on the administration of thoracic radiotherapy: the thoracic radiotherapy group ( n = 27) and the non-thoracic radiotherapy group ( n = 28). Comparative analyses were conducted to evaluate survival outcomes and safety profiles between the two groups. Results:Among the 55 patients, 27 (49.1%) received thoracic radiotherapy. The median follow-up time was 37.0 months (2.2-76.7 months). Patients in the thoracic radiotherapy group exhibited significantly improved median overall survival (OS: 53.4 vs. 21.3 months, P = 0.049) and median progression-free survival (PFS: 13.6 vs. 8.3 months, χ2=4.11, P = 0.043) compared to those in the non-thoracic radiotherapy group. Multivariate Cox regression analysis identified thoracic radiotherapy as an independent prognostic factor for OS ( HR = 0.39, 95% CI: 0.17-0.90, P = 0.027) and PFS ( HR = 0.53, 95% CI: 0.28-0.99, P = 0.046). The most common grade 3 or higher toxicity was bone marrow suppression, occurring in seven patients (12.7%). There was no significant difference between both groups in the incidence of grade 3 or higher treatment-related adverse events, including pneumonitis. Conclusion:In patients with driver gene-negative, synchronous oligometastatic NSCLC, first-line immunotherapy combined with thoracic radiotherapy may improve survival outcomes without increasing the incidence of severe treatment-related adverse events. Further large-scale, randomized prospective trials are needed to verify the findings of this study.

Background:Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials.Microbial agents,as environmentally friendly and efficient plant growth promoters and soil conditioners,have increasingly attracted attention in eco-agriculture research.Objective:Our understanding remains limited regarding how the application of microbial agents,alone or in combination,affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials.Methods:In this study,Epimedium pubescens Maxim.was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis)applied individually and in combination on plant growth and the accumulation of bioactive components.Additionally,this study explored the relationship between the rhizosphere microbiome and plant development.Results:The application of microbial agents increased the yield of E.pubescens leaves by 20.30％to 33.66％and enhanced the total flavonol glycosides content by 11.40％to 29.94％.Meanwhile,microbial treatments reshaped the rhizosphere microbiome,promoted the enrichment of beneficial microorganisms(e.g.,Frankia and Paenibacillus),suppressed phytopathogenic fungi such as Didymella and Scytalidium,and enhanced the stability of the soil microbial co-occurrence network.The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumula-tion of bioactive components by modulating the soil microbiome.Conclusion:These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere micro-biomes as mediated by microbial agents.They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.