Lymph node metastasis (LNM) is a crucial risk factor influencing an unfavorable prognosis in specific cancers. Fundamental research illuminates our understanding of tumor behavior and identifies valuable therapeutic targets. Nevertheless, the exploration of fundamental theories and the validation of clinical therapies hinge on preclinical experiments. Preclinical models, in this context, serve as the conduit connecting fundamental theories to clinical outcomes. In vivo models established in animals offer a valuable platform for comprehensively observing interactions between tumor cells and organisms. Using various experimental animals, including mice, diverse methods, such as carcinogen-induced tumorigenesis, tumor cell line or human tumor transplantation, genetic engineering, and humanization, have been used effectively to construct numerous models for tumor LNM. Carcinogen-induced models simulate the entire process of tumorigenesis and metastasis. Transplantation models, using human tumor cell lines or patient-derived tumors, offer a research platform closely mirroring the histology and clinical behavior of human tumors. Genetically engineered models have been used to delve into the mechanisms of primary tumorigenesis within an intact microenvironment. Humanized models are used to overcome barriers between human and murine immune systems. Beyond mouse models, various other animal models have unique advantages and limitations, all contributing to exploring LNM. This review summarizes existing in vitro and animal preclinical models, identifies current bottlenecks in preclinical research, and offers an outlook on forthcoming preclinical models.
Animals ; Humans ; Mice ; Lymphatic Metastasis/pathology* ; Disease Models, Animal ; Cell Line, Tumor

Protein arginine methyltransferase 5 (PRMT5) acts as an oncogene in liver cancer, yet its roles and in-depth molecular mechanisms within the liver cancer immune microenvironment remain mostly undefined. Here, we demonstrated that disruption of tumor-intrinsic PRMT5 enhances CD8⁺ T-cell-mediated antitumor immunity both in vivo and in vitro. Further experiments verified that this effect is achieved through downregulation of the inhibitory immune checkpoint molecule, fibrinogen-like protein 1 (FGL1). Mechanistically, PRMT5 catalyzed symmetric dimethylation of transcription factor 12 (TCF12) at arginine 554 (R554), prompting the binding of TCF12 to FGL1 promoter region, which transcriptionally activated FGL1 in tumor cells. Methylation deficiency at TCF12-R554 residue downregulated FGL1 expression, which promoted CD8⁺ T-cell-mediated antitumor immunity. Notably, combining the PRMT5 methyltransferase inhibitor GSK591 with PD-L1 blockade efficiently inhibited liver cancer growth and improved overall survival in mice. Collectively, our findings reveal the immunosuppressive role and mechanism of PRMT5 in liver cancer and highlight that targeting PRMT5 could boost checkpoint immunotherapy efficacy.

OBJECTIVE: Rhei Radix et Rhizoma has five types of products, namely, raw rhubarb (RR), wine rhubarb (WR), vinegar rhubarb (VR), cooked rhubarb (CR), and rhubarb charcoal (RC). However, Rhei Radix et Rhizoma is easily contaminated with fungi and mycotoxins if not harvested or processed properly. Here, we intend to analyze how microbiome assemblies and co-occurrence patterns are influenced by sampling locations and processing methods. METHODS: High-throughput sequencing and internal transcribed spacer 2 (ITS2) were carried out to study the diversities (α- and β-diversity), composition (dominant taxa and potential biomarkers), and network complexitity of surface fungi on RR, WR, VR, CR, and RC collected from Gansu and Sichuan provinces, China. RESULTS: The phyla Ascomycota and Basidiomycota; the genera Kazachstania, Malassezia, and Asterotremella; and the species Kazachstania exigua, Asterotremella pseudolonga, and Malassezia restricta were the dominant fungi and exhibited differences in the two provinces and the five processed products. The α-diversity and network complexity were strongly dependent on processing methods. Chao 1, the Shannon index, and network complexity and connectivity were highest in the CR group. The α-diversity and network complexity were influenced by sampling locations. Chao 1 and network complexity and connectivity were highest in the Gansu Province. CONCLUSION The assembly and network of the surface microbiome on Rhei Radix et Rhizoma were shaped by processing methods and sampling locations. This paper offers a comprehensive understanding of microorganisms, which can provide early warning for potential mycotoxins and ensure the safety of drugs and consumers.

OBJECTIVE: The investigation of the correlation between ecological factors and the genetic characteristics or metabolites of plants offers valuable insights into the regional causes of genetic and metabolic diversity. Here, Gastrodia elata, a medicinal plant, is employed as a model to explore the environmental factors that influence its genetic characteristics and metabolic accumulations. METHODS: A total of 23 G. elata populations from six cultispecies and 11 cultivated regions were selected based on the predictions of the global geographic information system. The genetic characteristics of these populations were evaluated using highly polymorphic simple sequence repeat markers. Additionally, the metabolic accumulations and antioxidant capacity of mature tubers were measured employing colorimetry and high performance liquid chromatography (HPLC). Ecological data of each region were obtained from the WorldClim-global climate database and harmonized world soil database. To assess the influence of ecological factors on the genetic characteristics and metabolic profiles of G. elata, Pearson's correlation analysis was conducted. RESULTS: Genetic variation among G. elata populations exceeded that within populations. Genetic diverisity, distance and structure manifested regional and species-specific patterns. Metabolic profiling and antioxidant capacity exhibited regional variations. Notably, the Lueyang region demonstrated that a content range of total polysaccharide, total protein, and phenolic glycosides was 9.34%-189.67% higher than the average. Similarly, in the Hubei region, total phenolic content, p-hydroxybenzyl alcohol content, and antioxidant indicators were observed to be higher than the average levels, by 106.57%, 136.47% and 12.50%-91.14%, respectively. Furthermore, ecological factors had a significant comprehensive impact on G. elata genetic characteristics (r > 0.256 and P < 0.05). Multivariate metabolite accumulations in G. elata were influenced by dominant ecological factors. Temperature notably impacted the accumulation of total protein (|r| > 0.528 and P < 0.05). Moisture, encompassing precipitation and soil content, significantly affected the production of phenolic glycosides (|r| > 0.503 and P < 0.05). CONCLUSION The genetic characteristics of G. elata manifested regional and species-specific patterns, with the metabolic accumulations and antioxidant capacity of mature tubers exhibited regional variations. Specifically, multivariate ecological factors comprehensively influenced genetic characteristics. Temperature and moisture played pivotal roles in regulating the accumulations of proteins and phenolic glycosides, respectively. These findings underscore the significant impact of ecological factors on the shaping of G. elata, highlighting their crucial role in enhancing the quality of Chinese medicinal materials.

In vitro,platelets are readily activated,which complicates the process of quality control.In con-trast,nanoparticles possess distinct advantages due to their small size,high surface area ratio,biocompatibili-ty,and modifiability.These properties enable them to inhibit platelet aggregation through encapsulation or multi-modification,thereby ensuring the stability of quality control products for clinical platelet assays.This paper delineates the properties of the two existent forms of platelet-nanoparticle complexes,their synthesis principles,and their applications in the medical field.The text goes on to examine the preparation methods of some platelet-nanoparticle complexes and their applications in the fields of cancer therapy,wound healing,and immune disorders.It also explores the potential relationship between platelet-nanoparticle complexes and exo-some-nanoparticle complexes.Additionally,the future research directions of nanoparticles in platelet plasmino-genics are discussed in this paper,emphasizing the effects of nanoparticle concentration,size,and surface modi-fication on platelet aggregation.This provides a theoretical basis for the development of stable and controllable platelet plasminogenics.

This paper aims to propose a noninvasive radiotherapy patient positioning system based on structured light surface imaging, and evaluate its clinical feasibility. First, structured light sensors were used to obtain the panoramic point clouds during radiotherapy positioning in real time. The fusion of different point clouds and coordinate transformation were realized based on optical calibration and pose estimation, and the body surface was segmented referring to the preset region of interest (ROI). Then, the global-local registration of cross-source point cloud was achieved based on algorithms such as random sample consensus (RANSAC) and iterative closest point (ICP), to calculate 6 degrees of freedom (DoF) positioning deviation and provide guidance for the correction of couch shifts. The evaluation of the system was carried out based on a rigid adult phantom and volunteers' body, which included positioning error, correlation analysis, and receiver operating characteristic (ROC) analysis. Using Cone Beam CT (CBCT) as the gold standard, the maximum translation and rotation errors of this system were (1.5 ± 0.9) mm along Vrt direction (chest) and (0.7 ± 0.3) ° along Pitch direction (head and neck). The Pearson correlation coefficient between results of system outputs and CBCT verification distributed in an interval of [0.80, 0.84]. Results of ROC analysis showed that the translational and rotational AUC values were 0.82 and 0.85, respectively. In the 4D freedom accuracy test on the human body of volunteers, the maximum translation and rotation errors were (2.6 ± 1.1) mm (Vrt direction, chest and abdomen) and (0.8 ± 0.4)° (Rtn direction, chest and abdomen) respectively. In summary, the positioning system based on structured light body surface imaging proposed in this article can ensure positioning accuracy without surface markers and additional doses, and is feasible for clinical application.
Humans ; Patient Positioning/methods* ; Phantoms, Imaging ; Cone-Beam Computed Tomography ; Algorithms ; Radiotherapy, Image-Guided/methods* ; Radiotherapy Planning, Computer-Assisted/methods*

Objective:To explore the value and related mechanism of preoperative serum sialic acid (SA) on evaluating microvascular invasion (MVI) in patients with intrahepatic cholangiocarcinoma (ICC).Methods:A total of 91 patients who underwent surgical resection and were pathologically diagnosed with ICC from December 2020 to September 2024 at the Oriental Hepatobiliary Surgery Hospital affiliated to the Naval Medical University were included in this retrospective analysis. The patients were divided into non-MVI (41 cases) and MVI groups (50 cases). The general data and laboratory examination indexes were collected and analyzed. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for predicting MVI. The predictive value of serum indicators for MVI was evaluated by receiver operating characteristic curves. The correlation between MVI and SA was analyzed by point-biserial correlation. ICC cells stably overexpressing β-galactoside α2, 6-sialyltransferase 1 (ST6GAL1) were generated through lentiviral transfection. ST6GAL1 protein expression and mRNA expression were detected by Western blot and quantitative real-time polymerase chain reaction, respectively. Sambucus nigra (SNA) lectin fluorescence staining was used to detect α2, 6-sialylation levels on cells. Cell migration ability was assessed by wound healing and Transwell assays, and cell proliferation was evaluated by colony formation assays.Results:Compared with the non-MVI group, patients in the MVI group exhibited significantly higher levels of fibrinogen, aspartate aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, SA and 5′-nucleotidase (5′-NT) (all P<0.05). Multivariate logistic regression analysis revealed that SA ( OR=1.01,95% CI 1.01-1.02, P=0.023) was the only independent predictor for MVI. The area under curve of SA in predicting MVI was 0.757 (95% CI 0.640-0.870), sensitivity 67.65%, specificity 77.78%. SA was positively correlated with MVI ( r=0.443, P<0.001). ICC cells overexpressing ST6GAL1 were featured with increased mean fluorescence intensity of SNA lectin, and increased level of α2, 6-sialylation on the cell surface (both P<0.05). The number of colonies formed by hypersialylated ICC cells was also increased ( P<0.05), and both the migration rate and the number of migrating cells were significantly higher ( P<0.05). Conclusions:Serum SA is an independent predictor for MVI in ICC patients. Hypersialylation in ICC cells is associated with higher malignancy.

Molecular diagnosis has become an important part in the field of precision medicine. With the continuous advancement of molecular diagnostic technologies, their significance in the field of precision medicine has grown, making molecular detection technologies and solutions increasingly important. There are still certain bottlenecks in the current molecular diagnostic approaches, that is, the level of automation in the detection process is insufficient to meet the growing efficiency needs for medical personnel. Although, molecular diagnostic automation has emerged, the existing automation technologies rely on automated equipment to assist laboratory personnel, which is not considered as full automation. In this study, we conducted an in-depth investigation and proposed two distinct solutions to address the current challenges: (1) point-of-care-testing (POCT)-based molecular diagnostic automation solution; (2) pipeline-based molecular diagnostic automation solution. We hope to provide better strategies to improve clinical laboratory testing capabilities and accuracy, and to guide future development of technology in the molecular diagnostic automation industry.

Many hematological disease prediction models built by big data analysis in medical laboratory and artificial intelligence (AI) technology, especially machine learning (ML) methods are reported more and more widely in researches on disease alerting, screening, diagnosis, discrimination, treatment and prediction. Because of a lack of guidance of standards, guidelines and normative documents in standardizing the construction and validation of these models, there is deficiency in model function, data preparation, screening and labeling, algorithm selection, model evaluation, as well as local and overall interpretation after model construction, which also limit the clinical application. Therefore, with integration of the literature review, combining the practice on blood disease prediction models, this article proposes that some keypoints and efficiency should be noticed, in order to build hematological diseases related models with clinical practical application value.

Objective:To analyze the values of platelet transforming growth factor-β (TGF-β) and SMAD family member 2 (Smad2) in patients′ peripheral platelets for CRC diagnosis and staging.Methods:Retrospective case-control study. Tumor tissues, paratumor tissues and peripheral blood samples were collected from 248 CRC patients (147 males, 101 females; age 21-93 years) diagnosed in the First Hospital of Jilin University from October 10th, 2020, to March 10th, 2025. Peripheral blood samples were also collected from 40 colorectal adenomatous polyp patients (21 males, 19 females; age 22-74 years) and 75 healthy individuals (43 males, 32 females; age 18-81 years) during the same period. Tissue homogenates and platelets were isolated using tissue disruption and gradient centrifugation, respectively. Total RNA was respectively extracted from tissues and platelets, and the expression levels of TGF-β and Smad2 were quantified by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) expressed as relative quantity 2 -ΔΔCt. Differences of TGF-β and Smad2 expression were compared between CRC tissues and adjacent tissues, as well as among CRC patients, polyp patients, and healthy controls. The relationship of platelet TGF-β and Smad2 expression with pathological features includingtumor stage, pathological type, and metastasis were analyzed. The efficiency of platelet TGF-β, Smad2, and their combination in diagnosing CRC was evaluated using receiver operating characteristic (ROC) curves. Results:The expression levels of TGF-β and Smad2 in CRC tumor tissues[1.09 (0.45, 2.00), 2.93 (0.78, 6.73)] were significantly higher than those in adjacent tissues[0.81 (0.27, 1.50), 1.29 (0.40, 2.63)] ( Z TGF-β=4.54, Z Smad2=6.67, both P<0.001). The expression levels of TGF-β and Smad2 in platelets of CRC patients[2.73(1.53, 4.38), 3.16 (1.58, 4.38)] were significantly higher than those in the colorectal polyp group[1.23(0.70, 2.54), 1.16(0.78, 2.27)] and the healthy control group[0.96(0.51, 1.88), 0.92 (0.55, 1.88)] ( H TGF-β=59.71, H Smad2=78.74, both P<0.001). Platelet TGF-β expression increased progressively with tumor stage (stage 1-4) ( P<0.05), while platelet Smad2 levels were higher in metastatic CRC compared with non-metastatic cases ( P<0.05). ROC curve analysis showed that the area under the curve (AUC) for diagnosing CRC when combining platelet TGF-β and Smad2 was 0.81[95%Confidence interval( CI) 0.77—0.86], which was 0.90 (95% CI 0.86—0.93) if adding serum carcinoembryonic antigen (CEA). Conclusion:Platelet TGF-β and Smad2 expression correlates with the diagnosis and staging of CRC, demonstrating potential as liquid biopsy biomarkers for colorectal malignancies.