Objective: To establish an accurate and rapid typing method for Rh typing of samples from patients who have received recent blood transfusions by utilizing the difference in osmotic fragility between fresh and old red blood cells. Methods: A lysing solution suitable for destroying old RBCs was prepared. Sixty-one samples collected in our hospital in 2024 with Rh typing of double groups were treated with the lysing solution to remove the old allogeneic red blood cells while preserving the patient's own fresh red blood cells, followed by repeat Rh typing tests. Results: For 61 samples with Rh typing in double groups, 41 were accurately detected identified through the red blood cell lysis method, yielding an identification rate of 67.21%. No significant difference was observed compared to the detection rate of the commonly used capillary centrifugation modified method (χ =0.103, P>0.05). Conclusion: The red blood cell lysis method provides a novel and rapid experimental approach for clinical use in processing Rh-typed samples that are of double groups, thereby offering a basis for Rh compatibility blood transfusion.

Objective: To provide evidence for improving emergency blood supply protocols by analyzing the clinical characteristics and disease distribution of emergency transfusion patients, especially those receiving≥10 units of red blood cells (RBCs). Methods: The data of 4 157 patients who urgently applied for large-volume blood transfusion in various hospitals in Shanghai from May 2024 to April 2025 were selected and analyzed statistically. Results: Tertiary gradeA hospitals accounted for the largest proportion of total transfusion volume (U) (48.79%, 8 420/17 256.5), with no statistically significant differences in RBC transfusion volumes among hospitals of different grades (P>0.05). All blood products are most widely used in tertiary hospitals. Obstetric blood transfusion (U)(19.07%, 3 277.5/17 190.5) was the most frequent. A-mong the hospitals of patients who received emergency blood transfusion with red blood cell suspension≥10 U, tertiary gradeA hospitals also had the largest transfusion volume (U)(47.19%, 1 107/2 346). In terms of disease types, the top three diseases in terms of blood transfusion volume (U) were obstetric transfusion (24.59%, 572/2 326), digestive diseases (14.53%, 338/2 326) and tumors (14.19%, 330/2 326). Conclusion: Tertiary grade A hospitals are the main demand units for emergency blood transfusion, with pregnant women and cancer patients being the core blood-using groups. It is suggested that the safety, timeliness and sufficiency of emergency blood transfusion be guaranteed by establishing a hierarchical blood supply mechanism, formulating single-disease blood transfusion plans and promoting precise blood transfusion guided by thromboelastography.

Objective To explore the clinical efficacy of robot-assisted coronary artery bypass grafting through a small incision in the left intercostal space in the treatment of multivessel coronary disease. Methods A retrospective analysis was conducted on the clinical data of patients who underwent coronary artery bypass grafting through a small incision in the left intercostal space at Central China Fuwai Hospital of Zhengzhou University from January 1, 2023 to October 15, 2024. Patients were divided into a robotic group and a minimally invasive group based on whether the surgery was assisted by the Da Vinci robot. Results A total of 81 patients were included, with 57 in the minimally invasive group, including 41 males and 16 females, with a median age of 65.0 (57.5, 69.5) years; and 24 in the robotic group, including 17 males and 7 females, with a median age of 61.0 (56.0, 69.0) years. There was no statistically significant difference in baseline data between the two groups (P>0.05). The robotic group had less intraoperative bleeding [300 (200, 438) mL vs. 500 (375, 600) mL, P=0.006], shorter postoperative mechanical ventilation time [15.0 (13.3, 23.5) h vs. 22.0 (15.5, 39.5) h, P=0.037], and lower incidence of postoperative pain [8 (33.3%) vs. 33 (57.9%), P=0.043]. The hospitalization cost in the robotic group was higher than that in the minimally invasive group [130491 (123298, 135691) yuan vs. 123892 (115543, 133449) yuan, P=0.023]. There was no statistical difference in postoperative laboratory indicators between the two groups (P>0.05). There was also no statistical difference in the duration of surgery, postoperative 24 h drainage volume, ICU stay time, postoperative hospital stay or incidences of perioperative compications including pleural effusion, transfusion, new-onset atrial fibrillation, acute kidney injury, non-union of incision, major cardiovascular and cerebrovascular adverse events, and reoperation between the two groups (P>0.05). Conclusion Compared with the minimally invasive group, the robotic group shows satisfactory efficacy and can effectively reduce postoperative pain and intraoperative bleeding, and shorten postoperative mechanical ventilation time.

Objective: To address the challenges of systematically identifying herb pairs in traditional Chinese medicine (TCM), we proposed HerbGL, a framework for predicting potential herb pairs that integrates network propagation and graph regularization. Methods: Based on the assumption that herbal actions induce subtle perturbations in biological systems, a framework named HerbGL was proposed. Random walk with restart (RWR) was first applied to the protein-protein interaction (PPI) network to reconstruct herb-specific perturbation effects and generate weighted subnetworks. Then, to quantify affinity between herb pairs, two network-proximity metrics, Closeness and PageRank, were computed from the weighted subnetworks to construct herb-pair affinity matrices. Finally, these matrices, together with known herb pairs (derived from co-occurrence analysis of TCM formulas with a threshold determined from the inflection point of the frequency distribution), were incorporated into a graph regularization model to predict potential herb pairs. Model performance was assessed through baseline comparison, ablation and robustness experiment under different ratios of positive and negative samples, using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), accuracy, and precision as evaluation metrics. Furthermore, the predicted herb pairs were validated through both literature evidence and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Results: The weighted subnetworks constructed by RWR provided a refined simulation of herb-specific perturbation effects, which formed the basis for subsequent affinity modeling and prediction. Analysis of herb pair co-occurrence frequencies revealed a marked change around 150, which was selected as the threshold to distinguish herb pairs from non-herb pairs. HerbGL exhibited superior predictive performance compared with baseline models (AUROC = 0.970 5, AUPRC = 0.955 5, accuracy = 0.726 6, precision = 0.970 6). Ablation results showed that removing the Closeness and PageRank metrics substantially degraded performance (AUROC = 0.819 1, AUPRC = 0.876 8), confirming their necessity. Robustness evaluation under an imbalanced positive-to-negative sample ratio of 1 : 5 yielded AUROC = 0.969 6 and AUPRC = 0.840 4, indicating stable predictive ability. Moreover, multiple case studies further validated the rationality of the predicted herb pairs, such as Fangfeng (Saposhnikoviae Radix) and Qingpi (Citri Reticulatae Pericarpium Viride) which are recorded in Liangpeng Huiji (《良朋汇集》, Collection of Excellent Recipes) Vol. 3: Fangfeng Shengma Tang (防风升麻汤). Additionally, pathway enrichment analysis of the Renshen (Ginseng Radix et Rhizoma) and Lianqiao (Forsythiae Fructus) pair further supported the biological plausibility of their compatibility. Conclusion HerbGL offers an effective and biologically informed framework for identifying herb pairs in TCM. Beyond improving herb pair prediction, the framework also provides data support for research on herb compounds and mechanisms, thereby supporting data-driven exploration of TCM compatibility.

Objective: To address systemic challenges in the blood system, such as supply-demand imbalance, inefficient allocation, and inappropriate clinical use, while bridging gaps in current theories regarding the integration of social mobilization, institutional practice, and policy coordination. It sought to construct a system dynamics model spanning from macro to micro levels to analyze the blood management system holistically. Methods: Key variables were identified by a systematic literature search in both Chinese and English databases. An improved Delphi method was then employed to conduct expert consultations across different fields, leading to the selection and determination of core variable sets for each sub-model. Furthermore, by defining their logical relationships, a system dynamics model was constructed to systematically analyze the operation mechanism of the blood management system. Results: Four core sub-models were developed: 1) A macro "Dynamic Balance" model quantifying regional supply-demand equilibrium and inventory control; 2) a mobilization "Three-Layer Funnel" model analyzing how socio-cultural factors, service channels, and policy incentives influence donation behavior; 3) an institutional "Dual-Cycle Regulation" model revealing hospital blood usage is driven by both disease burden (demand cycle) and management practices (regulation cycle); and 4) an individual "Three-Layer Filter" model standardizing clinical transfusion decisions based on necessity, risk-benefit, and context. These were integrated into a "Multi-Layer Linkage and Feedback" model, elucidating bidirectional interactions among five levels: policy environment, regional supply, blood station mobilization, hospital application, and clinical decision-making. Conclusion: This study constructed a system dynamics model for blood management. By defining key variables and their logical relationships, it systematically analyzes the system′s operational mechanism. The integrated framework connects multiple levels—regional supply, voluntary donation, hospital blood use, and clinical decision-making—revealing their intrinsic linkages. Future efforts should employ systems thinking to synergistically enhance supply-side mobilization, demand-side management, systemic regulation, and decision standardization to build a safe, efficient, and sustainable blood security system.

Lung transplantation is a definitive treatment for end-stage lung disease and can significantly improve patient prognosis. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury and chronic lung allograft dysfunction intertwine to form a complex pathological network, posing persistent challenges to long-term patient survival. In 2025, research teams worldwide have made systematic progress in the field of basic lung transplantation research. By integrating cutting-edge technologies including single-cell multi-omics, spatial transcriptomics and novel animal models, significant breakthroughs have been achieved in the evolutionary dynamics of drug-resistant infections, molecular mechanisms of immune regulation, programmed cell death, optimization of donor lung protection strategies and early warning of chronic lung allograft dysfunction. This article systematically reviews the representative advances in basic lung transplantation research worldwide in 2025, and deeply analyzes the implications of mechanistic breakthroughs for optimizing diagnosis and treatment strategies, aiming to anchor the direction for innovative breakthroughs and clinical translation in basic lung transplantation research.

Metastatic dissemination is the major cause of death from breast-cancer (BC). Fusobacterium nucleatum (F.n) is widely enriched in BC and has recently been identified as one of the high-risk factors for promoting BC metastasis. Here, with an experimental model, we demonstrated that intratumoral F.n induced BC aggressiveness by transcriptionally activating Epithelial-mesenchymal transition-associated genes. Therefore, the F.n may be a potential target to prevent metastasis. Given the fact that cancer-associated fibroblasts (CAFs) are abundant in BC and located near blood vessels, we report an optogenetic system that drives CAF to in situ produce human antibacterial peptide LL37, with the characteristics of biosafety and freely intercellular trafficking, for depleting intratumoral F.n, leading to a 72.1% reduction in lung metastatic nodules number without affecting the balance of the systemic flora. Notably, mild photothermal treatment was found that could normalize CAF, contributing to synergistically inhibiting BC metastasis. In addition, the system can also simultaneously encode a gene of TNF-related apoptosis-inducing ligand to suppress the primary tumor. Together, our study highlights the potential of local elimination of tumor pathogenic bacteria to prevent BC metastasis.

Objective To explore the prognostic value of glycolysis-related genes in colorectal cancer (CRC) patients and formulate a novel glycolysis-related prognostic risk model. Methods Single-cell and bulk transcriptomic data of CRC patients, along with clinical information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Glycolysis scores for each sample were calculated using single-sample Gene Set Enrichment Analysis (ssGSEA). Kaplan-Meier survival curves were generated to analyze the relationship between glycolysis scores and overall survival. Novel glycolysis-related subgroups were defined among the cell type with the highest glycolysis scores. Gene enrichment analysis, metabolic activity assessment, and univariate Cox regression were performed to explore the biological functions and prognostic impact of these subgroups. A prognostic risk model was built and validated based on genes significantly affecting the prognosis. Gene Set Enrichment Analysis (GSEA) was conducted to explore differences in biological processes between high- and low-risk groups. Differences in immune microenvironment and drug sensitivity between these groups were assessed using R packages. Potential targeted agents for prognostic risk genes were predicted using the Enrichr database. Results Tumor tissues showed significantly higher glycolysis scores than normal tissues, which was associated with a poor prognosis in CRC patients. The highest glycolysis score was observed in epithelial cells, within which we defined eight novel glycolysis-related cell subpopulations. Specifically, the P4HA1⁺ epithelial cell subpopulation was associated with a poor prognosis. Based on signature genes of this subpopulation, a six-gene prognostic risk model was formulated. GSEA revealed significant biological differences between high- and low-risk groups. Immune microenvironment analysis demonstrated that the high-risk group had increased infiltration of macrophages and tumor-associated fibroblasts, along with evident immune exclusion and suppression, while the low-risk group exhibited higher levels of B cell and T cell infiltration. Drug sensitivity analysis indicated that high-risk patients were more sensitive to Abiraterone, while low-risk patients responded to Cisplatin. Additionally, Valproic acid was predicted as a potential targeted agent. Conclusion High glycolytic activity is associated with a poor prognosis in CRC patients. The novel glycolysis-related prognostic risk model formulated in this study offers significant potential for enhancing the diagnosis and treatment of CRC.
Humans ; Colorectal Neoplasms/pathology* ; Glycolysis/genetics* ; Prognosis ; Transcriptome ; Tumor Microenvironment/genetics* ; Gene Expression Profiling ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Male ; Female ; Kaplan-Meier Estimate

Biosensors have become powerful tools for real-time monitoring of specific small molecules and precise control of gene expression in biological systems. High-throughput sensors for 1, 4-butanediamine biosynthesis can greatly improve the screening efficiency of high-yielding 1, 4-butanediamine strains. However, the strategies for adapting the characteristics of biosensors are still rarely studied, which limits the applicability of 1, 4-butanediamine biosensors. In this paper, we propose the development of a 1, 4-butanediamine biosensor based on the transcriptional regulator PuuR, whose homologous operator puuO is installed in the constitutive promoter P_gapA of Escherichia coli to control the expression of the downstream superfolder green fluorescent protein (sfGFP) as the reporter protein. Finally, the biosensor showed a stable linear relationship between the GFP/OD₆₀₀ value and the concentration of 1, 4-butanediamine when the concentration of 1, 4-butanediamine was 0-50 mmol/L. The promoters with different strengths in the E. coli genome were used to modify the 1, 4-butanediamine biosensor, and the functional properties of the PuuR-based 1, 4-butanediamine biosensor were explored and improved, which laid the groundwork for high-throughput screening of engineered strains highly producing 1, 4-butanediamine.
Biosensing Techniques/methods* ; Escherichia coli/metabolism* ; Promoter Regions, Genetic/genetics* ; Green Fluorescent Proteins/metabolism* ; Transcription Factors/genetics* ; Escherichia coli Proteins/genetics* ; Diamines/metabolism* ; Gene Expression Regulation, Bacterial

Objective:To develop and assess a deep learning-based model for automatic segmentation of organs at risk (OARs) in postoperative brachytherapy for endometrial carcinoma (EC).Methods:A retrospective study was conducted on the computed tomography (CT) images of 108 EC patients who received high-dose-rate (HDR) 192Ir intracavitary vaginal-cuff brachytherapy (VCB) at the Peking University Third Hospital from November 2021 to October 2022. Then, the rectum, colon, small intestine, and bladder in these images were manually segmented. These patients were randomly divided into two groups using a random number table: 90 cases for training the 3D no-new-U-Net (nnU-Net) segmentation model and 18 cases for model testing. The precision and clinical applicability of the automatic segmentation model were assessed using geometric indexes including Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD), as well as dose-volume parameters (DVPs) including the minimum dose to 0.1, 1.0, and 2.0 cm 3 of OARs that received the highest irradiation doses ( D0.1 cm 3, D1.0 cm 3, and D2.0 cm 3). Results:The 3D nnU-Net model yielded mean DSC values of 0.90, 0.85, 0.88, and 0.95, respectively for the segmentations of the rectum, colon, small bowel, and bladder, all of which were better than those of the 3D U-Net and V-Net models. The differences among the three models were statistically significant ( F = 21.78, 24.33, 36.00, 20.11, P < 0.001). The 3D nnU-Net exhibited statistically significant differences in HD values for the colon, small intestine, and bladder segmentations among the three method ( F = 17.33, 24.11, 6.33, P < 0.05). The 3D nnU-Net model yielded lower MSD values for the segmentations of all organs compared to the control model, with statistically significant differences ( F = 29.78, 27.11, 27.11, 14.78, P < 0.001). No statistically significant difference was found in all DVPs between the 3D nnU-Net model-based and manual segmentations ( P > 0.05). Bland-Altman analysis demonstrated great consistency between the 3D nnU-Net and manual segmentations. Conclusions:The 3D nnU-Net-based model exhibits high geometric accuracy and dosimetric consistency with manual segmentation of OARs in brachytherapy, holding potential to improve clinical efficiency.