Objective:To analyze the clinical characteristics of children with head and neck rhabdomyosarcoma (RMS) and to summarize the mid-long term efficacy of Beijing Children′s Hospital Rhabdomyosarcoma 2006 (BCH-RMS-2006) regimen and China Children′s Cancer Group Rhabdomyosarcoma 2016 (CCCG-RMS-2016) regimen.Methods:A retrospective cohort study. Clinical data of 137 children with newly diagnosed head and neck RMS at Beijing Children′s Hospital, Capital Medical University from March 2013 to December 2021 were collected. Clinical characteristic of patients at disease onset and the therapeutic effects of patients treated with the BCH-RMS-2006 and CCCG-RMS-2016 regimens were compared. The treatments and outcomes of patients with recurrence were also summarized. Survival analysis was performed by Kaplan-Meier method, and Log-Rank test was used for comparison of survival rates between groups.Results:Among 137 patients, there were 80 males (58.4%) and 57 females (41.6%), the age of disease onset was 59 (34, 97) months. The primary site in the orbital, non-orbital non-parameningeal, and parameningeal area were 10 (7.3%), 47 (34.3%), and 80 (58.4%), respectively. Of all patients, 32 cases (23.4%) were treated with the BCH-RMS-2006 regimen and 105 (76.6%) cases were treated with the CCCG-RMS-2016 regimen. The follow-up time for the whole patients was 46 (20, 72) months, and the 5-year progression free survival (PFS) and overall survival (OS) rates for the whole children were (60.4±4.4)% and (69.3±4.0)%, respectively. The 5-year OS rate was higher in the CCCG-RMS-2016 group than in BCH-RMS-2006 group ((73.0±4.5)% vs. (56.6±4.4)%, χ2=4.57, P=0.029). For the parameningeal group, the 5-year OS rate was higher in the CCCG-RMS-2016 group (61 cases) than in BCH-RMS-2006 group (19 cases) ((57.3±7.6)% vs. (32.7±11.8)%, χ2=4.64, P=0.031). For the group with meningeal invasion risk factors, the 5-year OS rate was higher in the CCCG-RMS-2016 group (54 cases) than in BCH-RMS-2006 group (15 cases) ((57.7±7.7)% vs. (30.0±12.3)%, χ2=4.76, P=0.029). Among the 10 cases of orbital RMS, there was no recurrence. In the non-orbital non-parameningeal RMS group (47 cases), there were 13 (27.6%) recurrences, after re-treatment, 7 cases survived. In the parameningeal RMS group (80 cases), there were 40 (50.0%) recurrences, with only 7 cases surviving after re-treatment. Conclusions:The overall prognosis for patients with orbital and non-orbital non-parameningeal RMS is good. However, children with parameningeal RMS have a high recurrence rate, and the effectiveness of re-treatment after recurrence is poor. Compared with the BCH-RMS-2006 regimen, the CCCG-RMS-2016 regimen can improve the treatment efficacy of RMS in the meningeal region.

BACKGROUND:Black phosphorus has a high degree of homology with human bone,so it has been extensively studied in the field of bone tissue engineering in recent years.Since 2014,two-dimensional black phosphorus materials have garned significant attention in the field of biomedicine due to their excellent exceptional physical,chemical,and biological properties. OBJECTIVE:To summarize the advancements made in black phosphorus-based nanomaterials for bone tissue engineering,focus on the synthesis methods,osteogenic characteristics,and applications in biomaterials pertaining to two-dimensional black phosphorus nanomaterials. METHODS:Chinese and English key words were"black phosphorus,bone tissue engineering,bone defect,bone regeneration,osteogenesis."Relevant articles in PubMed and CNKI databases from January 2014 to December 2023 were searched.After exclusion and screening,96 articles were analyzed. RESULTS AND CONCLUSION:Black phosphorus nanomaterials play an important role in bone tissue engineering due to their good biocompatibility,biodegradability,photothermal action,antibacterial ability,drug loading performance,and special osteogenic effect,and are ideal candidate materials for promoting bone regeneration.The preparation of black phosphorus nanomaterials is mainly a top-down top-layer stripping method.The main principle is to weaken the van der Waals force between the black phosphorus layers by physical or chemical means to obtain a single or less layer of phosphanse,that is,black phosphorus nanosheets or quantum dots.Black phosphate-based nanocomposites are mainly divided into hydrogels,3D printing scaffolds,composite scaffolds,electrospinning,bionic periosteum,microspheres,and bionic coatings.The research of nano-black phosphorus in bone tissue engineering is in its infancy,and still faces many challenges:the behavior of black phosphorus in vivo and the interaction mechanism with various biomolecules need to be further studied.The long-term potential toxicity of black phosphorus is unknown.The manufacturing process for black phosphorus is difficult to control.Therefore,how to develop uniform size,safe,reliable,and efficient nano black phosphorus and transform it into clinical application requires interdisciplinary research on modern biomedical technology,physicochemical technology,and precision manufacturing technology.

The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

Cell models can simulate a variety of life states and disease developments, including single cells, two-dimensional (2D) cell cultures, three-dimensional (3D) multicellular spheroids, and organoids. They are essential tools for addressing complex biochemical questions. With continuous advancements in biological and cellular analysis technologies, in vitro cellular models designed to answer scientific questions have evolved rapidly. Early in vitro models primarily relied on 2D systems, which failed to accurately replicate the complex cellular compositions and microenvironmental interactions observed in vivo, let alone support sophisticated investigations into cellular biological functions. Subsequent improvements in cell culture techniques led to the development of 3D culture-based models, such as cellular spheroids. The advent of pluripotent stem cell technology further advanced the development of organoid systems, which closely mimic human organ development. Compared to traditional 2D models, both 3D cellular models and organoids offer significant advantages, including personalization and enhanced physiological relevance, making them particularly suitable for exploring molecular mechanisms of disease progression, discovering novel cellular and biomolecular functions, and conducting related studies. The imaging analysis of common cellular models primarily employs labeling-based methods for in situ imaging of targeted genes, proteins, and small-molecule metabolites, enabling further research on cell types, states, metabolism, and drug efficacy. However, these approaches have drawbacks such as poor labeling specificity and complex experimental procedures. By using cells as experimental models, mass spectrometry technology combined with morphological analysis can reveal quantitative changes and spatial distributions of various biological substances at the spatiotemporal level, including metabolites, proteins, lipids, peptides, drugs, environmental pollutants, and metals. This allows for the investigation of cell-cell interactions, tumor microenvironments, and cellular bioinformational heterogeneity. The application of these cutting-edge imaging technologies generates vast amounts of cellular data, necessitating the development of rapid, efficient, and highly accurate image data algorithms for precise segmentation and identification of single cells, multi-organelle structures, rare cell subpopulations, and complex cellular morphologies. A critical focus lies in creating deep learning models and algorithms that enhance the accuracy of cellular visualization. At the same time, establishing more robust data integration tools is essential not only for analyzing and interpreting outputs but also for effectively uncovering the biological significance of spatially resolved mass spectrometry data. Developing a cell imaging platform with high versatility, operational stability, and specificity to enable data interoperability will significantly enhance its utility in clinical research, thereby advancing investigations into disease molecular mechanisms and supporting precision diagnostics and therapeutics. In contrast to genomic, transcriptomic, and proteomic information, the metabolome can rapidly respond to external stimuli and cellular physiological changes within a short timeframe. This rapid and precise reflection of ongoing cellular state alterations has positioned spatial metabolomics as a pivotal approach for exploring the molecular mechanisms underlying physiological and pathological processes in cells, tissues, and organisms. In this review, we summarize research on cell imaging based on mass spectrometry technologies, including the selection and preparation of cell models, morphological analysis of cell models, spatial omics techniques based on mass spectrometry, mass cytometry, and their applications. We also discuss the current challenges and propose future directions for development in this field.

Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.

ObjectiveJunctophilin-2 (JPH2) is an essential structural protein that maintains junctional membrane complexes (JMCs) in cardiomyocytes by tethering the plasma membrane to the sarcoplasmic reticulum, thereby facilitating excitation-contraction (E-C) coupling. Mutations in JPH2 have been associated with hypertrophic cardiomyopathy (HCM), but the molecular mechanisms governing its membrane-binding properties and the functional relevance of its membrane occupation and recognition nexus (MORN) repeat motifs remain incompletely understood. This study aimed to elucidate the structural basis of JPH2 membrane association and its implications for HCM pathogenesis. MethodsA recombinant N-terminal fragment of mouse JPH2 (residues1-440), encompassing the MORN repeats and an adjacent helical region, was purified under near-physiological buffer conditions.X-ray crystallography was employed to determine the structure of the JPH2 MORN-Helix domain. Sequence conservation analysis across species and junctophilin isoforms was performed to assess the evolutionary conservation of key structural features. Functional membrane-binding assays were conducted using liposome co-sedimentation and cell-based localization studies in COS7 and HeLa cells. In addition, site-directed mutagenesis targeting positively charged residues and known HCM-associated mutations, including R347C, was used to evaluate their effects on membrane interaction and subcellular localization. ResultsThe crystal structure of the mouse JPH2 MORN-Helix domain was resolved at 2.6 Å, revealing a compact, elongated architecture consisting of multiple tandem MORN motifs arranged in a curved configuration, forming a continuous hydrophobic core stabilized by alternating aromatic residues. A C-terminal α-helix further reinforced structural integrity. Conservation analysis identified the inner groove of the MORN array as a highly conserved surface, suggesting its role as a protein-binding interface. A flexible linker segment enriched in positively charged residues, located adjacent to the MORN motifs, was found to mediate direct electrostatic interactions with negatively charged phospholipid membranes. Functional assays demonstrated that mutation of these basic residues impaired membrane association, while the HCM-linked R347C mutation completely abolished membrane localization in cellular assays, despite preserving the overall MORN-Helix fold in structural modeling. ConclusionThis study provides structural insight into the membrane-binding mechanism of the cardiomyocyte-specific protein JPH2, highlighting the dual roles of its MORN-Helix domain in membrane anchoring and protein interactions. The findings clarify the structural basis for membrane targeting via a positively charged linker and demonstrate that disruption of this interaction—such as that caused by the R347C mutation—likely contributes to HCM pathogenesis. These results not only enhance current understanding of JPH2 function in cardiac E-C coupling but also offer a structural framework for future investigations into the assembly and regulation of JMCs in both physiological and disease contexts.

BACKGROUND: The potential impact of pre-existing coronary artery stenosis (CAS) on right ventricular (RV) function during acute pulmonary embolism (PE) episodes remains underexplored. This study aimed to investigate the association between pre-existing CAS and RV dysfunction in patients with acute PE. METHODS: In this multicenter, case-control study, 89 cases and 176 controls matched for age were enrolled at three study centers (Peking Union Medical College Hospital, Fuwai Hospital, and the Second Affiliated Hospital of Harbin Medical University) from January 2016 to December 2020. The cases were patients with acute PE with CAS, and the controls were patients with acute PE without CAS. Coronary artery assessment was performed using coronary computed tomographic angiography. CAS was defined as ≥50% stenosis of the lumen diameter in any coronary vessel >2.0 mm in diameter. Conditional logistic regression analysis was used to evaluate the association between CAS and RV dysfunction. RESULTS: The percentages of RV dysfunction (19.1% [17/89] vs. 44.6% [78/176], P <0.001) and elevated systolic pulmonary artery pressure (sPAP) (19.3% [17/89] vs. 39.5% [68/176], P = 0.001) were significantly lower in the case group than those in the control group. In the multivariable logistic regression model, CAS was independently and negatively associated with RV dysfunction (adjusted odds ratio [OR]: 0.367; 95% confidence interval [CI]: 0.185-0.728; P = 0.004), and elevated sPAP (OR: 0.490; 95% CI: 0.252-0.980; P = 0.035), respectively. CONCLUSIONS Pre-existing CAS was significantly and negatively associated with RV dysfunction and elevated sPAP in patients with acute PE. This finding provides new insights into RV dysfunction in patients with acute PE with pre-existing CAS.
Humans ; Pulmonary Embolism/complications* ; Case-Control Studies ; Male ; Ventricular Dysfunction, Right/physiopathology* ; Female ; Middle Aged ; Aged ; Coronary Stenosis/complications* ; Logistic Models ; Adult

This article systematically reviews the characteristics and trends of the writing, editing, publication and promotion of physiology textbooks in China from the late 19th century to the present, focusing on the introduction, development and innovation of Chinese physiology textbooks. The development of physiology textbooks in China is divided into four main stages: the introduction and initial development of physiology textbooks from the late 19th century to 1925; the localization and diversification of textbooks from 1926 to 1949, after the establishment of the Chinese Physiological Society; the exploratory phase of textbook construction after the founding of the People's Republic of China from 1949 to 1976; the formation and innovation of the textbook development process from 1977 to the present, following the restoration of the college entrance examination. For each phase, the article not only records the historical development of physiology textbooks, but also analyzes the evolution of their content, writing styles and the interaction with the social and political contexts. The article summarizes the characteristics and experiences of all these four phases. Special attention is given to the comprehensive statistical analysis of physiology textbooks published since the restoration of the college entrance examination and Economic Reform and Opening-up in 1977, revealing the changes in the number, publication trends and academic features of textbooks during this period. Finally, the article presets the future development of physiology textbooks in China, proposing that textbook writing should integrate aspects such as ideological and political education, medical humanities, basic and clinical medicine, health education, scientific research and international exchange and collaboration. The article also advocates for the application of new technologies and methods, such as artificial intelligence, virtual teaching models and knowledge graphs, to support "personalized learning". This research provides a systematic reference for the study of the history of medical education and offers theoretical support for the future innovation of physiology textbook in China.
Humans ; China ; History, 19th Century ; History, 20th Century ; History, 21st Century ; Physiology/education* ; Textbooks as Topic/history*

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

This study aims to investigate the ameliorating effect of Corni Fructus(CF) on the myocardial ischemic injury and the pharmacokinetic properties of characteristic components of CF. The mouse model of isoproterenol-induced myocardial ischemia was established and administrated with the aqueous extract of CF. The general efficacy of CF in ameliorating the myocardial ischemic injury was evaluated based on the cardiac histopathology and the levels of myocardial injury markers: creatine kinase isoenzyme(CK-MB) and cardiac troponin I(cTn-I). The metabolomics analysis was carried out for the heart and serum samples of mice to screen the biomarkers of CF in ameliorating the myocardial ischemic injury and then the predicted biomarkers were submitted to metabolic pathway enrichment. The pharmacokinetic analysis was performed for morroniside, loganin, and cornuside Ⅰ in mouse heart and serum samples to obtain the pharmacokinetic parameters of these components. The pharmacokinetic parameters were then integrated on the basis of self-defined weighting coefficients to simulate an integrated pharmacokinetic profile of CF iridoid glycosides in the heart and serum of the mouse model of myocardial ischemia. The results indicated that CF reduced the pathological damage to cardiac cells and tissue(hematoxylin-eosin staining) and lowered the levels of CK-MB and cTn-I in the serum of the mouse model of myocardial ischemia(P<0.01). Metabolomics analysis screed out 31 endogenous metabolites in the heart and 35 in the serum as biomarkers of CF in ameliorating the myocardial ischemic injury. These biomarkers were altered by modeling and restored by CF. Six metabolic pathways in the heart and 5 in the serum were enriched based on these metabolic markers. The main integrated pharmacokinetic parameters of CF iridoid glycosides were T_(max)=1 h, t_(1/2)=(1.52±0.05) h in the heart and T_(max)=1 h, t_(1/2)=(1.56±0.50) h in the serum. Both concentration-time curves showed a double-peak phenomenon. In conclusion, CF demonstrated the cardioprotective effect by regulating metabolic pathways such as taurine and hypotaurine metabolism, and pantothenic acid and coenzyme A biosynthesis. The integrated pharmacokinetics reflect the general pharmacokinetic properties of characteristic components in CF.
Animals ; Cornus/chemistry* ; Mice ; Metabolomics ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Myocardial Ischemia/metabolism* ; Humans ; Troponin I/metabolism* ; Myocardium/pathology* ; Disease Models, Animal ; Biomarkers/metabolism* ; Creatine Kinase, MB Form/metabolism*