ObjectiveThis paper aims to investigate the material basis of the anti-inflammatory efficacy and mechanism of action of Bushen Tongdu prescription （BSTDP）. MethodsThe chemical components of BSTDP and its blood-absorbed components in vivo were systematically identified by using ultra-performance liquid chromatography-linear ion trap-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-LIT-Orbitrap-MS）. Network pharmacology was employed to screen blood-absorbed bioactive components and potential targets of this formula. A protein-protein interaction （PPI） network of core targets was constructed to conduct enrichment analysis. Molecular docking was further utilized to verify the binding affinity between key components and targets. The inflammatory model was established and verified in vivo by using a transgenic zebrafish Tg （mpx： GFP）. At three days post-fertilization （3 dpf）， larvae of zebrafish were randomly assigned to blank group， model group， positive drug dexamethasone acetate group （75 μmol·L^-1）， and BSTDP groups with low， medium， and high doses （500， 1 000， and 2 000 mg·L^-1）. The distribution and quantity of neutrophils in the yolk sac region were observed under a fluorescence microscope. The mRNA expression levels of key genes in the toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor kappa-B （NF-κB） signaling pathway and inflammatory factors including interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） were detected by Real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsA total of 120 chemical components were identified in BSTDP， among which 26 original components were confirmed by using serum pharmacochemical methods. A total of 227 common targets linking rheumatoid arthritis （RA） and the blood-absorbed components were screened by network pharmacology. It is suggested that pseudobrucine， vomicine， sinapine， rehmannioside， cinnamyl alcohol glycoside， and methylephedrine exert anti-inflammatory effects by acting on core targets including protein kinase B1 （Akt1）， signal transducer and activator of transcription 3 （STAT3）， tumor necrosis factor （TNF）， TLR4， mitogen-activated protein kinase 14 （MAPK14）， and phosphatidylinositol-4，5-bisphosphate 3-kinase catalytic subunit α （PIK3CA）， thereby modulating multiple signaling pathways such as TLR4 and NF-κB. In vivo verification in zebrafish demonstrates that the maximum tolerable concentration of Bushen Tongdu Formula is 2 000 mg·L^-1. Compared to those in the blank group， zebrafish in the model group showed a significantly higher number of neutrophils in the yolk sac region （P<0.01） and rising mRNA levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β （P<0.01）. Compared to that in the model group， the number of neutrophils was significantly reduced in BSTDP groups with medium and high doses， as well as the dexamethasone acetate group （P<0.05， P<0.01）. There was no statistically significant difference in the low dose group. The mRNA expression levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β were significantly down-regulated （P<0.05， P<0.01）. ConclusionThis paper identifies the material basis of the efficacy of BSTDP， demonstrating that the formula can exert an anti-inflammatory effect through the TLR4/MyD88/NF-κB signaling pathway. The results provide scientific experimental evidence for its further clinical application.

ObjectiveThis paper aims to investigate the material basis of the anti-inflammatory efficacy and mechanism of action of Bushen Tongdu prescription （BSTDP）. MethodsThe chemical components of BSTDP and its blood-absorbed components in vivo were systematically identified by using ultra-performance liquid chromatography-linear ion trap-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-LIT-Orbitrap-MS）. Network pharmacology was employed to screen blood-absorbed bioactive components and potential targets of this formula. A protein-protein interaction （PPI） network of core targets was constructed to conduct enrichment analysis. Molecular docking was further utilized to verify the binding affinity between key components and targets. The inflammatory model was established and verified in vivo by using a transgenic zebrafish Tg （mpx： GFP）. At three days post-fertilization （3 dpf）， larvae of zebrafish were randomly assigned to blank group， model group， positive drug dexamethasone acetate group （75 μmol·L^-1）， and BSTDP groups with low， medium， and high doses （500， 1 000， and 2 000 mg·L^-1）. The distribution and quantity of neutrophils in the yolk sac region were observed under a fluorescence microscope. The mRNA expression levels of key genes in the toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor kappa-B （NF-κB） signaling pathway and inflammatory factors including interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） were detected by Real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsA total of 120 chemical components were identified in BSTDP， among which 26 original components were confirmed by using serum pharmacochemical methods. A total of 227 common targets linking rheumatoid arthritis （RA） and the blood-absorbed components were screened by network pharmacology. It is suggested that pseudobrucine， vomicine， sinapine， rehmannioside， cinnamyl alcohol glycoside， and methylephedrine exert anti-inflammatory effects by acting on core targets including protein kinase B1 （Akt1）， signal transducer and activator of transcription 3 （STAT3）， tumor necrosis factor （TNF）， TLR4， mitogen-activated protein kinase 14 （MAPK14）， and phosphatidylinositol-4，5-bisphosphate 3-kinase catalytic subunit α （PIK3CA）， thereby modulating multiple signaling pathways such as TLR4 and NF-κB. In vivo verification in zebrafish demonstrates that the maximum tolerable concentration of Bushen Tongdu Formula is 2 000 mg·L^-1. Compared to those in the blank group， zebrafish in the model group showed a significantly higher number of neutrophils in the yolk sac region （P<0.01） and rising mRNA levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β （P<0.01）. Compared to that in the model group， the number of neutrophils was significantly reduced in BSTDP groups with medium and high doses， as well as the dexamethasone acetate group （P<0.05， P<0.01）. There was no statistically significant difference in the low dose group. The mRNA expression levels of TLR4， MyD88， NF-κB， TNF-α， IL-6， and IL-1β were significantly down-regulated （P<0.05， P<0.01）. ConclusionThis paper identifies the material basis of the efficacy of BSTDP， demonstrating that the formula can exert an anti-inflammatory effect through the TLR4/MyD88/NF-κB signaling pathway. The results provide scientific experimental evidence for its further clinical application.

ObjectiveTo establish a mouse model of hypoxic pulmonary hypertension (HPH) through intermittent hypoxia induction, and to develop a comprehensive and reliable evaluation system for the HPH model, thereby providing experimental evidence for mechanistic studies and translational applications related to this disease. MethodsTwenty-four male specific pathogen-free (SPF) BALB/c mice were randomly divided into a control group and a model group, with 12 mice per group. Mice in the model group were placed in a hypobaric oxygen chamber control system to establish the HPH model, whereas mice in the control group received no intervention. After 28 days of modeling, a comprehensive evaluation of the pathophysiological characteristics of both groups was performed using a general condition scoring scale, echocardiography, hemodynamic measurements, blood gas analysis, hematological tests, organ coefficient determination, histopathological examination, and enzyme-linked immunosorbent assay (ELISA). In addition, correlation analyses were conducted among echocardiographic parameters, the contents of endothelin‑1 (ET‑1) and N‑terminal pro‑B‑type natriuretic peptide (NT‑proBNP) in lung tissue, and other measured indices. ResultsWith prolonged modeling duration time, body weight, water intake, and activity level of mice in the model group were significantly decreased compared with the control group (P<0.05). Echocardiography showed that, compared with the control group, the model group exhibited increased right ventricular dimensions (P<0.01), right ventricular anterior wall thickening (P<0.01), and widened main pulmonary artery diameter (P<0.01), whereas the peak systolic velocity across the pulmonary valve, tricuspid annular plane systolic excursion, and peak systolic velocity of the tricuspid annulus were significantly decreased (P<0.001); tricuspid regurgitation was observed in some model animals. Hemodynamic results revealed that right ventricular systolic pressure was elevated in the model group compared with the control group (P<0.001). Blood gas analysis showed that pH, partial pressure of oxygen, oxygen saturation, actual bicarbonate, and total carbon dioxide were all decreased in the model group compared with the control group (P<0.01). Hematological indices demonstrated that lymphocyte counts (P<0.05) and reticulocyte counts (P<0.001) were decreased in the model group compared with the control group. Compared with the control group, the organ coefficients of heart and lung in the model group were significantly increased (P<0.05 and P<0.001). Pathological examination revealed that the right ventricular hypertrophy index was significantly increased in the model group (P<0.001), with varying degrees of damage to the right ventricle, pulmonary artery, and pulmonary vessels; both the pulmonary artery wall thickness percentage and the pulmonary wall area percentage were significantly elevated (P<0.001). ELISA results showed that the levels of ET‑1 and NT‑proBNP in lung tissues were significantly increased in the model group compared with the control group (P<0.05 and P<0.001, respectively). Correlation analysis indicated that some echocardiographic parameters were highly correlated with multiple indices in the development of HPH (P<0.05). ConclusionEchocardiography can accurately assess a series of hemodynamic changes in HPH, including right ventricular structural, functional impairment, and pulmonary hypertension. Laboratory tests not only help verify whether the model has been successfully established, but also provide deeper insights into the pathogenesis of HPH, evaluate the effects of interventions, and offer scientific evidence for clinical outcomes. Pathological examination can further confirm the alterations in pulmonary vascular remodeling and increased right heart load. This multimodal analysis provides a reliable animal model and evaluation paradigm for both basic and translational research on HPH, and is of great significance for exploring disease mechanisms and developing precision therapeutic strategies.

Background: Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder. Cellular drug screening represents a key approach in the preclinical discovery of AD therapeutics. Moreover, selecting an appropriate cellular model is essential for exploring the mechanisms underlying AD pathogenesis. Objective: This study aimed to establish a progressive strategy integrating cell model construction, monomer evaluation, and effective component group-based drug discovery for the development of novel therapeutics targeting AD. Methods: A novel AD12 cell line stably expressing the double-transgenic genes amyloid precursor protein (APP)695/presenilin 1(PS1)-ΔE9 was first constructed and subjected to lipopolysaccharide (LPS) stimulation. The resulting LPS-induced neuroinflammatory response was characterized using metabolomic analysis. Subsequently, 16 alkaloids derived from traditional Chinese medicine(TCM) were screened with the LPS-AD12 cell model. Molecular docking was then performed to assess the binding affinity of benzoylaconitine (BAC) with APP and PS1 proteins. A targeted metabolomics approach focusing on amino acids and the tricarboxylic acid (TCA) cycle was applied to BAC-treated LPS-AD12 cells. Finally, aconite extract was administered to five-familial-AD-mutations(5xFAD) transgenic mice, and therapeutic efficacy was evaluated through phenotypic and metabolomic analyses. Results: LPS stimulation induced neuroinflammation in AD12 cells, characterized by elevated levels of interleukin-6, amyloid-β (Aβ ), and PS1. The primary metabolic pathways affected in AD12 cells included alanine, aspartate, and glutamate metabolism, as well as arginine biosynthesis. Notably, BAC significantly reduced the levels of Aβ and interleukin-6 in LPS-AD12 cells. Furthermore, molecular docking analyses revealed a strong binding affinity of BAC with APP and PS1 proteins. Targeted metabolomics analysis indicated that the pharmacological activity of BAC was primarily associated with its anti-inflammatory effects, modulation of the cholinergic signaling pathway, and regulation of energy metabolism. Behavioral experiments in 5xFAD mice, together with immunofluorescence assessments of brain tissues (amyloid-β, glial fibrillary acidic protein, and ionized calcium-binding adapter molecule 1), demonstrated that aconite extract treatment significantly alleviated AD-related symptoms. In addition, metabolomics-based mechanistic analyses revealed that serine, acetylcholine, ornithine, and gamma-aminobutyric acid exhibited consistent trends in both brain tissue and serum samples from treated mice. Conclusion: This study established a novel AD12 cell model and an effective, reliable LPS-induced cell-based screening system. Additionally, we proposed a new drug discovery strategy integrating cell model construction, monomer evaluation, and effective component group-based drug discovery. This screening system has the potential to accelerate the identification of anti-AD agents and provides a feasible framework for subsequent in-depth investigations into new drug development from TCM, thereby contributing to the modernization of TCM-derived therapeutics.

ObjectiveTo screen and identify uridine diphosphate （UDP）-rhamnose synthase （RHM） genes from Ornithogalum saundersiae and verify their UDP-rhamnose （UDP-Rha） biosynthetic functions， thereby providing reliable candidate genes for the efficient biosynthesis of neohesperidin and other rhamnoside natural products. MethodsBased on previously reported plant RHM sequences， two candidate RHM genes， OsRHM1 and OsRHM2， were identified from O. saundersiae through transcriptome screening and sequence alignment. The two genes were cloned and subjected to bioinformatics analysis and multiple sequence alignment. An in vitro RHM-Cm1，2RhaT cascade reaction was established， and the ability of OsRHM1 and OsRHM2 to catalyze the conversion of UDP-glucose （UDP-Glc） to UDP-Rha was evaluated based on neohesperidin production. Real-time fluorescence quantitative polymerase chain reaction PCR （Real-time PCR） was performed to analyze the relative expression levels of the two genes in roots， bulbs， and leaves. ResultsThe open reading frame （ORF） of OsRHM1 was 2 076 bp and encoded 692 amino acids， with a predicted protein molecular mass of 77.97 kDa and a theoretical isoelectric point of 7.25. The ORF of OsRHM2 was 2 019 bp and encoded 673 amino acids， with a predicted protein molecular mass of 75.82 kDa and a theoretical isoelectric point of 7.24. Multiple sequence alignment showed that OsRHM1 and OsRHM2 contained the typical conserved motifs GxxGxxG/A and YxxxK of the plant RHM family and shared high amino acid sequence identity with previously reported RHMs. The in vitro cascade reaction demonstrated that both OsRHM1 and OsRHM2 were capable of catalyzing the conversion of UDP-Glc to UDP-Rha. The neohesperidin production in the OsRHM2 cascade reaction system was approximately 2.58-fold that in the OsRHM1 system. Real-time PCR analysis showed that the relative expression levels of OsRHM1 and OsRHM2 were higher in roots than in bulbs and leaves. ConclusionOsRHM2 exhibited a relatively high capacity for UDP-Rha supply and may serve as a candidate enzyme resource for the subsequent biosynthesis of rhamnoside natural products and the construction of UDP-Rha supply systems.

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

Many triterpenoid compounds have been successfully heterologously synthesized in Saccharomyces cerevisiae. To increase the yield of triterpenoids, various metabolic engineering strategies have been developed. One commonly applied strategy is to enhance the supply of precursors, which has been widely used by researchers. Squalene, as a precursor to triterpenoid biosynthesis, plays a crucial role in the synthesis of these compounds. This study primarily investigates the effect of different squalene levels in chassis strains on the synthesis of triterpenoids(oleanolic acid and ursolic acid), and the underlying mechanisms are further explored using real-time quantitative PCR(qPCR) analysis. The results demonstrate that the chassis strain CB-9-5, which produces high levels of squalene, inhibits the synthesis of oleanolic acid and ursolic acid. In contrast, chassis strains with moderate to low squalene production, such as Y8-1 and CNPK, are more conducive to the synthesis of oleanolic acid and ursolic acid. The qPCR analysis reveals that the expression levels of ERG1, βAS, and CrCYP716A154 in the oleanolic acid-producing strain CB-OA are significantly lower than those in the control strains C-OA and Y-OA, suggesting that high squalene production in the chassis strains suppresses the transcription of certain genes, leading to a reduced yield of triterpenoids. Our findings indicate that when constructing S. cerevisiae strains for triterpenoid production, chassis strains with high squalene content may suppress the expression of certain genes, ultimately lowering their production, whereas chassis strains with moderate squalene levels are more favorable for triterpenoid biosynthesis.
Squalene/analysis* ; Saccharomyces cerevisiae/genetics* ; Triterpenes/metabolism* ; Metabolic Engineering ; Oleanolic Acid/biosynthesis* ; Ursolic Acid

Objective To observe the morphology of the superficial,middle,and deep layers of the masseter muscle and related bony structures in the lateral facial region of adults through gross anatomy,and to probe into the effects of these muscle layers on the bony structures of the lateral facial region.Methods The bilateral masseter muscles of 12 adult cadavers were exposed,and the superficial,middle,and deep layers were separated and measured for muscle length,tendon length,and muscle belly length.After the masseter muscles were stripped,the total thickness was measured,and the mandible and zygomatic arch were exposed to measure the angle of the mandibular angle,thickness of the zygomatic arch,and width of the zygomatic arch.Observations were made of the masseter tuberosities,and statistical analysis was conducted on their interrelations.Results The zygomatic arch thickness was positively correlated with the length of superficial,middle and deep masseter muscles and the length of superficial and middle masseter belly(r superficial masseter length=0.624,r middle masseter length=0.787,r deep masseter length=0.423,r superficial masseter belly length=0.493,r middle masseter belly length=0.548).The width of the zygomatic arch was positively correlated with the lengths of the superficial and middle muscle layers and the middle muscle belly length(r superficial masseter length=0.527,r middle masseter length=0.521,r middle masseterbelly length=0.437).The angle of the mandibular angle was only negatively correlated with the middle muscle belly length(r=-0.422).The tuberosities of the superficial and middle masseter muscles were not affected by the corresponding muscle layers;However,the tuberosity of the deep masseter was negatively correlated with the length of the deep muscle and the length of the deep tendon(r deep masseter length=-0.543,r deep masseter tendon length=-0.443).Conclusion In the masseter muscle layers of Chinese individuals,the superficial and middle layers have the most significant impact on the bony structures structures of the lateral facial region.These findings are of guiding significance for the remodeling of structures in the lateral facial region.

By selecting stable and detectable drug prototypes or metabolites in sewage samples, near real-time detection of disease conditions can be achieved. This study selected oseltamivir carboxylate, the primary metabolite of first-line antiviral oseltamivir, as a biomarker. Based on the concentration of oseltamivir carboxylate in wastewater, the consumption and usage rate of oseltamivir were calculated by reverse engineering. Quarterly sampling was conducted at 46 urban sewage treatment plants in representative 5 cities in the middle and lower reaches of the Yangtze River, from November 2022 to December 2023. The concentration range of oseltamivir acid in sewage samples is 1.270−1 279 ng/L, the daily mass load of oseltamivir per 1 000 inhabitants in the surveyed cities ranged from 9.560 to 544.7 mg/d, and the average utilization rate is 0.06‰−3.63‰. The research results indicate that in March 2023, Wuxi City experienced a spring influenza peak, while Bengbu, Tongling, Suzhou, and Changzhou City experienced a small summer influenza peak in May. In November and December 2023, Wuxi, Changzhou, and Bengbu City experienced a winter influenza peak, the results are consistent with the official statistics of the National Center for Disease Control and Prevention and the National Influenza Center, which reflect the influenza epidemic situation in southern cities. The integration of this methodology with clinical diagnostic rates could provide near real-time data support for future influenza prevention and control strategies.

Objective:To address the inefficiency, safety hazards, and resource wastage in traditional medical laboratory management, this study proposes a digital laboratory information management system (LIMS) based on Total Quality Management (TQM) principles. The LIMS has been implemented at the National Center for Geriatric Medicine (Huashan) affiliated with Fudan University.Methods:Centered on the principles of " all-staff participation, whole-process control, and comprehensive management", a multidimensional management framework was developed to integrate personnel, equipment, reagents, and safety protocols. The system incorporated IoT, digital twin, and artificial intelligence (AI) technologies to achieve end-to-end digital control. A layered architecture (physical layer, data layer, model layer, etc.) was designed to integrate functional modules such as full lifecycle equipment management, dual-authentication for hazardous chemicals, and intelligent resource scheduling. A 3D digital twin model was deployed to visualize real-time laboratory operations.Results:Post-implementation, equipment reservation frequency and usage duration at the National Center increased by 114% and 124%, respectively, with no safety incidents reported. Equipment sharing utilization reached 85%, and reagent expiration waste decreased by 30%.Conclusions:The system transforms laboratory management from experience-driven to data-driven by breaking data silos and optimizing collaboration mechanisms. It provides a replicable technical pathway and practical insights for the healthcare industry′s digital transformation. However, further improvements are needed in mobile support and system scalability.