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.

In March 2024, three male and two female specimens of the genus Lispe were intercepted on cargo ships inbound for Wan Zai Port under Gongbei Customs. Based on morphological characteristics and molecular analysis, the specimens were identified as Lispe pumila. In this study, we describe the morphological features, diagnostic characteristics, and geographical distribution of L. pumila, with the aim of providing a reference for the identification of this species when intercepted at ports.

ObjectiveThis paper aims to investigate the intervention effect and molecular mechanism of Gancao Fuzitang （GCFZT） in knee osteoarthritis （KOA）. MethodsNetwork pharmacology was employed to predict the key targets and signaling pathways of GCFZT. Fifty SD rats were randomly divided into a sham group， a model group （KOA）， a low-dose GCFZT group （GCFZT-L， 2.8 g·kg^-1）， a high-dose GCFZT group （GCFZT-H， 5.6 g·kg^-1）， and a positive drug celecoxib group （Celecoxib， 20 mg·kg^-1）， with 10 rats in each group. The rats in the sham group and the model group were given an equal volume of distilled water. Except for the sham group， the other four groups underwent anterior cruciate ligament transection to establish the KOA rat model. After successful modeling， the rats in each group received intragastric administration once a day for eight consecutive weeks. The structural changes of cartilage and subchondral bone were assessed via micro-computed tomography （micro-CT） and histological staining. The levels of inflammatory factors in the serum， such as interleukin-1β （IL-1β）， IL-6， and tumor necrosis factor-α （TNF-α） were measured using an enzyme linked immunosorbent assay （ELISA） kit. Real-time quantitative polymerase chain reaction （Real-time PCR）， Western blot， and immunohistochemistry were used to detect changes in the expression of autophagy-related proteins such as microtubule-associated protein 1 light chain 3B （LC3B）， selective autophagy junction protein 62 （p62）， and autophagy key molecule yeast Atg6 homolog （Beclin-1） in articular cartilage， as well as key molecules of the phosphatidylinositol 3 kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR） signaling pathway. ResultsNetwork pharmacology analysis suggests that GCFZT may exert anti-osteoarthritic effects through regulating the PI3K/Akt/mTOR pathway. In vivo experiment shows that GCFZT can significantly improve cartilage degeneration and attenuate subchondral bone destruction in KOA rats. Detection results of inflammatory factors in the serum reveal that， compared with those in the sham group， the levels of IL-6， IL-1β， and TNF-α in the serum of rats in the KOA group are significantly increased （P<0.05）. Compared with those in the KOA group， the levels of these three inflammatory factors in the GCFZT-L， GCFZT-H， and Celecoxib groups were significantly decreased （P<0.05）. However， there was no statistically significant difference in these three inflammatory factor levels between the GCFZT-H group and the celecoxib group. These findings suggest that GCFZT can effectively inhibit the systemic inflammatory response in KOA rats. Mechanism research indicates that GCFZT inhibits activation of the PI3K/Akt/mTOR pathway， thereby enhancing autophagic activity and improving chondrocyte function and matrix degeneration. ConclusionGCFZT improves cartilage and subchondral bone damage in KOA rats by inhibiting the PI3K/Akt/mTOR signaling pathway and promoting autophagy. These findings provide theoretical evidence for the application of GCFZT in the prevention and treatment of osteoarthritis.

Core fucosylation, catalyzed exclusively by fucosyltransferase 8 (FUT8), is an evolutionarily conserved post-translational modification that has emerged as a central regulatory hub linking liver homeostasis, chronic disease progression, and malignant transformation. Liver diseases, particularly hepatocellular carcinoma, remain a leading global health burden characterized by late diagnosis, limited therapeutic options, and poor overall survival. While aberrant glycosylation is now recognized as a hallmark of cancer and inflammatory disorders, existing research on FUT8-mediated core fucosylation in liver diseases remains fragmented: the dynamic functional switch of FUT8 from a homeostatic regulator to a pathological driver across the full disease continuum has not been systematically delineated, and the integrated mechanisms by which core fucosylation modulates oncogenic signaling, metabolic reprogramming, and immune evasion remain poorly understood. This review synthesizes recent advances to establish a unified framework for understanding the dual role of core fucosylation in liver physiology and pathology, and evaluates its translational potential for precision medicine. At the molecular level, FUT8’s unique catalytic specificity makes core fucosylation an irreplaceable modification, as evidenced by the perinatal lethality and severe organ dysfunction in Fut8 knockout mice. In hepatocellular carcinoma, genomic amplification of guanosine 5'-diphosphate-fucose biosynthetic enzymes provides metabolic support for aberrant core fucosylation. FUT8 expression is tightly regulated by a multi-layered network: transcriptional activation via Wnt/β‑catenin and wild-type p53, epigenetic upregulation by lncRNAs, post-transcriptional repression by miR-122-5p and miR-34a, and virus-specific induction by hepatitis B virus/hepatitis C virus. Physiologically, core fucosylation maintains liver homeostasis through four core mechanisms: it acts as a molecular switch for epidermal growth factor receptor/hepatocyte growth factor receptor signaling to enable liver regeneration; directs polarized secretion of hepatocyte-derived glycoproteins into bile ducts; modulates cholesterol metabolism via the hepatocyte nuclear factor 1α-proprotein convertase subtilisin/kexin type 9-low density lipoprotein receptor axis; and regulates aging through insulin‑like growth factor 1 receptor signaling. Pathologically, core fucosylation exhibits context-dependent dual functions: in liver fibrosis, FUT8 upregulation in hepatic stellate cells forms a negative feedback loop that limits excessive fibrogenesis; in hepatocellular carcinoma, however, aberrant FUT8 overexpression drives cell-autonomous malignancy by constitutively activating epidermal growth factor/hepatocyte growth factor receptor, transforming growth factor‑β/Smad, and Wnt/β‑catenin pathways, while simultaneously establishing a multi-layered immune evasion network by stabilizing programmed cell death ligand 1 and cluster of differentiation 47, and impairing natural killer cell homeostasis via interleukin‑2 receptor β glycosylation. Clinically, stage-specific core fucosylation biomarkers enable non-invasive monitoring of liver disease progression: low molecular mass kringle-Fc fusion protein outperforms conventional markers for early fibrosis detection, while alpha-fetoprotein-L3 and novel glycopeptides (α‑2‑macroglobulin N‑linked glycosylation site 1424, lumican core fucosylated peptide) significantly improve early hepatocellular carcinoma diagnosis, especially in alpha-fetoprotein-negative patients. Next-generation detection technologies (chemoenzymatic labeling, site-specific mass spectrometry) overcome the specificity limitations of traditional lectin assays. Therapeutically, four promising strategies are emerging: small-molecule FUT8 inhibitors, afucosylated antibodies with enhanced antibody‑dependent cellular cytotoxicity, Fuc-modified targeted drug delivery systems, and core fucose-specific lectins for NASH treatment. The core challenge for clinical translation lies in FUT8’s inherent “double-edged sword” effect, as systemic inhibition disrupts its essential physiological functions beyond pathological roles. Long-term systemic FUT8 blockade not only impairs post-injury liver regeneration by abrogating epidermal growth factor/hepatocyte growth factor receptor signaling but also disrupts cholesterol homeostasis via the hepatocyte nuclear factor 1α-proprotein convertase subtilisin/kexin type 9-low density lipoprotein receptor axis, leading to dyslipidemia and altered bile secretion. Critically, it compromises immune surveillance by destabilizing interleukin‑2 receptor β on natural killer cells, reducing their cytotoxic activity against malignant and virally infected cells, and impairs IgG Fc-mediated effector functions, increasing susceptibility to infections. This fundamental trade-off between therapeutic efficacy and systemic toxicity necessitates a paradigm shift from non-specific global inhibition to precision modulation of pathological core fucosylation. By addressing these critical challenges, FUT8-mediated core fucosylation has the potential to transform liver disease management from late-stage intervention to early detection and precision therapy, ultimately improving patient outcomes and reducing the global burden of liver diseases.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Objective:This study aimed was to analyze the disease progression of postoperative recurrence/me-tastasis of pancreatic ductal adenocarcinoma(PDAC)and provide clinical evidence for evaluating the difference in prog-nosis between site and pattern of recurrence/metastasis.Methods:The clinical data of 167 patients with PDAC who underwent pancreatectomy in Panjin Liao-Oil Gem Flower Hospital from January 2011 to June 2019 were retrospec-tively analyzed.Kaplan-Meier curves and Cox-regression analyses were applied to assess survival outcomes.Results:In this study,96 patients(57.5%)recurred within 12 months after surgery,and the median recurrence time was 10.9 months.Compared to patients without recurrence,patients with recurrence/metastasis had higher baseline CA19-9>100 IU/mL and were treated more often with neoadjuvant chemotherapy(P<0.05).In the no recurrence group,patients had histopathological analyses yielded lower less poorly differentiated tumors,less positive margin,less pT3+4 stages and pN1+2 stages(P<0.05).In a multivariate Cox regression analysis,receipt of neoadjuvant chemotherapy,poor tumor differ-entiation and positive margin were independent predictors for recurrence/metastasis within 12 months after surgery(P<0.05).Neoadjuvant treated patients had less pT1+2 stages(P=0.015),a lower lymph node ratio,less perineural invasion,less positive margin,and were less likely to be treated with adjuvant chemotherapy compared to upfront surgery treated patients(P<0.05).Recurrence/metastasis rates were higher in the neoadjuvant treated cohort versus the upfront surgery cohort(P=0.014).There was no statistical difference in the recurrence/metastasis rate distribution between neoadjuvant therapy and upfront surgery,and neoadjuvant therapy exhibited no significant impact on recurrence/metastasis patterns in PDAC(P>0.05).The overall survival period of patients without recurrence/metastasis within 12 months was signifi-cantly longer than that of patients with recurrence/metastasis after PDAC resection(P<0.001).Conclusion:The varying site recurrence/metastasis rates and time to recurrence/metastasis,underline the inherent heterogeneity of PDAC and the specific interactions in the tumor microenvironments at the recurrence/metastasis sites.Further research is essential to establish optimal personalized treatment strategies for patients with recurrent PDAC.

Hypercholesterolemia is pathologically characterized by abnormal accumulation of low-density lipoprotein cholesterol,which is closely associated with metabolic dysfunction-associated fatty liver disease and increased cardiovascular risks.Hepatocytes maintain cholesterol homeostasis through LDL receptor-mediated uptake and esterification storage mechanisms.However,chronic cholesterol overload induces mitochondrial dysfunction,reactive oxygen species accumulation,and endoplasmic reticulum stress,leading to hepatocyte injury.Moreover,systemic hypercholesterolemia disrupts gut microbiota balance and impairs short-chain fatty acid and ketone metabolism,exacerbating metabolic disturbances and aggravating hepatic injury through enhanced metabolic stress.In this article,we review the advance of studies on hypercholesterolemia in recent years and summary its association with hepatic injury,which can provide theoretical support for further research.

Epilepsy,as the second most common neurological disease,has diverse causes,complex,difficult to treat,and disabling characteristics,which impose a heavy burden on patients' families and social life.Long term recurrent epileptic seizures and poor control lead to neuronal inactivation and cognitive impairment in patients.Therefore,it is becoming increasingly important to find new targeted treatment methods and explore the molecular regulatory mechanisms of epilepsy on neuronal damage.Iron induced cell death is a novel programmed cell death mediated by ferrous ions,characterized by the accumulation of ferrous ions,harmful lipid peroxides,and lethal reactive oxygen species,leading to damage to mitochondrial function and structure.With recent in-depth research on ferroptosis,it has been found that inhibiting ferroptosis related targets and pathways can alleviate seizures and progression of epilepsy and protect neurons.This article provides a brief overview of the molecular mechanisms and related regulation of ferroptosis,its role in epilepsy,and recent advances in related treatments.

Aim To investigate the effect of high-fat diet on the tight junction function injury of Sertoli cells through the NF-κB/NLRP3 signaling pathway in mice and to explore the underlying mechanism.Methods Male C57BL/6J mice were fed with high-fat or normal diet for five months.The body and gonadal organ weight of mice were measured,and their indices were calculated.The sperm concentration,the sperm viabili-ty,the testicular histomorphology and the expression levels of tight junction proteins ZO-1,Occludin and Claudin-11 were measured.TM4 cells were treated with palmitic acid(PA)for 24 h.Cell viability was detected by CCK-8 method.Then,TM4 cells were di-vided into different groups treated with PA(0,50,100,200 and 300 μmnol·L-1),and the expression lev-els of tight junction proteins ZO-1,Occludin and Clau-din-11 were detected by Western blot.The tight junc-tion permeability of TM4 cells were detected by transepithelial electrical resistance(TEER)and FITC-dextran.The expression levels of mRNA and proteins for the NF-κB/NLRP3 pathway-related factors were de-tected by RT-qPCR and Western blot.Results The results from animal experiments showed that high-fat diet increased body weight and seminal vesicle weight of mice,and decreased testicular index,epididymal in-dex,sperm concentration and sperm motility of mice.High-fat diet also caused testicular tissue structure damage and down-regulated the expression levels of tight junction proteins ZO-1 and Occludin,without af-fecting the expression of Claudin-11.In vitro,PA sig-nificantly down-regulated the expression levels of ZO-1,Occludin and Claudin-11 in TM4 cells,increased the cell permeability,as well as up-regulated the mRNA and protein expression levels of NLRP3/NF-κB signa-ling pathway-related factors in TM4 cells.Conclusions High-fat diet can impair the function of tight junction of testicualr Sertoli cells,and the machanism may be related to the activation of the NF-κB/NLRP3 signaling pathway,resulting in Sertoli cell inflammation in mice.