Objective: To report the antibody identification, blood management during pregnancy and the monitoring process of fetal hemolytic disease of fetus and newborn (HDFN) in a pregnant woman with a history of blood transfusion and pregnancy who developed anti-Jr . Methods: Saline tube technique and anti-human globulin technique were used for maternal blood typing, unexpected antibody screening and identification, as well as for determining antibody titer and IgG subclasses. PCR-SSP was employed for genotyping of 18 blood group systems. Next-generation sequencing (NGS) was utilized for gene sequencing of 38 blood group systems. Sanger sequencing was applied to verify rare blood group mutations detected by NGS and to investigate the corresponding rare blood group genes in family members. Blood preparation was achieved through anemia management in prenatal clinics and autologous blood collection during pregnancy. The newborn underwent the three primary tests for HDFN and plasma IgG subclass testing. Results: The pregnant woman's blood type was B, RhD positive, with a positive unexpected antibody screen, and the antibody identification pattern was consistent with a high-frequency antigen antibody. Gene sequencing revealed a homozygous ABCG2 c.376C>T mutation in the woman, resulting in the Jr(a-) phenotype, and anti-Jr antibody was present in her plasma. No compatible Jr(a-) blood was found among family members. The maternal anti-Jr IgG titer remained stable at 256 during pregnancy, with no detectable IgG1 or IgG3 subclasses against the Jr antigen. A total of 800 mL of autologous blood was collected in two stages during pregnancy. The newborn was B, RhD positive, Jr(a+), with a positive unexpected antibody screen (anti-Jr ). IgG subclass typing detected no IgG1 or IgG3. The direct antiglobulin test was positive, while the acid elution test was negative. Conclusion: The combination of serology and blood group genetic analysis provides a diagnostic basis for identifying antibodies to high-frequency antigens. Managing perinatal anemia and implementing staged autologous blood storage can secure blood supply for the perioperative period. IgG antibody subclass typing offers a reference for clinical assessment and prevention of HDFN.

Objective: To investigate the effects of a Twin-Block appliance combined with slow maxillary expansion (SME) on transverse dental and skeletal parameters in adolescent patients with Angle Class Ⅱ division 1 malocclusion, and to provide a reference for clinical orthodontic practice. Methods: This retrospective study was approved by the Institutional Ethics Committee. A total of 21 adolescents with Class Ⅱ division 1 malocclusion who underwent two-phase treatment with a Twin-Block appliance combined with SME at the Department of Orthodontics, College & Hospital of Stomatology, Guangxi Medical University, in 2021 to 2023 were consecutively enrolled. In the first phase, a functional appliance was used to coordinate the skeletal relationship between the maxilla and mandible by leveraging growth potential. In the second phase, a fixed appliance was employed for fine adjustments of the dental arches based on the specific condition. Cone-beam computed tomography (CBCT) scans were obtained before treatment (T0) and after the first phase of functional correction (T1). Transverse measurements at the first molar region, including molar buccolingual inclination, dental arch width, and basal bone width, were performed using Dolphin 3D Imaging software. Changes between T0 and T1 were statistically analyzed. Results: After the first phase of treatment, the left and right maxillary first molars showed a significant increase in buccal inclination by 5.47° ± 1.38° and 5.35° ± 1.61°, respectively (P<0.001). The arch width in the maxillary first molar region also increased by (2.68 ± 1.14) mm, and the basal bone width increased by (1.14 ± 1.24) mm (all P<0.001). The proportion of skeletal expansion accounted for an average of 42.86%, while dental expansion accounted for 57.14%. No statistically significant changes were observed in any mandibular transverse measurements (all P>0.05). Conclusion In adolescent patients with Angle Class Ⅱ division 1 malocclusion accompanied by maxillary transverse deficiency, Twin-Block appliance combined with SME can effectively expand maxillary dental arch and basal bone width while improving sagittal relationship, thereby correcting transverse discrepancy. The maxillary width changes were predominantly dental.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveAs a common lifestyle habit, alcohol consumption has a controversial association with the onset of Parkinson’s disease (PD). To demonstrate the correlation between alcohol consumption and PD and to identify associated genes, we integrated findings from clinical surveys, genomics, transcriptomics, and animal experiments. MethodsWe investigated the alcohol consumption rates (including both before and after disease onset) among 244 PD patients in China and 177 PD patients from the U.S. NHANES database. Mendelian randomization (MR) analysis was performed using genome-wide association study (GWAS) data for three alcohol-related traits and seven PD-related datasets from the MRC IEU OpenGWAS database. Transcriptomic data from the substantia nigra of PD patients were obtained from three GEO datasets (GSE7621, GSE20141, and GSE49036) to analyze RIT2 gene transcription. Finally, three groups of animal experiments (water/20% ethanol/20% liquor, with 4 C57BL/6J mice per group) were conducted to examine changes in brain RIT2 gene expression and transcriptomic profiles following alcohol consumption. ResultsThe alcohol consumption rates among PD patients in China and the U.S. (9%-18.87%) were significantly lower than the general population rates of 15%-45% in their respective regions (P<0.001), suggesting a possible negative association between alcohol consumption and PD. Subsequently, in 21 bidirectional MR analyses using 3 alcohol-related GWAS datasets and 7 PD-related GWAS datasets, the forward MR analyses (alcohol intake as exposure, PD as outcome) yielded 12 negative associations (OR_IVW<1) and 9 positive associations (OR_IVW>1). Among these, only two negative associations reached statistical significance: alcohol intake frequency (OR_IVW=0.75, 95% CI: 0.60-0.93, P=0.010) and alcohol consumption (OR_IVW=0.20, 95% CI: 0.05-0.83, P=0.026). The forward MR analysis (alcohol intake→PD) identified 235 SNPs, annotated to 316 genes, while the reverse MR analyses (PD→alcohol intake) identified 37 SNPs, annotated to 53 genes. Notably, only the RIT2 gene appeared in both the forward and reverse MR analyses (alcohol intake→PD: rs28597806, rs8083110; PD→alcohol intake: rs4588066). RIT2 is selectively expressed in the human brain (FPKM: 5.259±2.103), with low or no expression in peripheral tissues (FPKM: <1). Analysis of three human substantia nigra transcriptomic datasets revealed a decreasing trend in RIT2 gene expression in PD patients (GSE20141 array signal: 3.49±1.23 vs. 2.33±0.87, P=0.044). Animal experiments demonstrated that administration of 20% ethanol or 20% liquor (approximately 8% ethanol) stimulated a >2-fold upregulation of RIT2 gene expression in the mouse brain. Furthermore, transcriptomic sequencing revealed that the two alcohol-treated groups exhibited 96 (20% ethanol vs. water control) and 4 (20% liquor vs. water control) differentially expressed genes, respectively, indicating that low-dose alcohol consumption can achieve RIT2 upregulation while minimizing impact on other brain genes. In addition to its anti-infective effects, low-dose alcohol consumption primarily influences signaling pathways related to neurodegenerative diseases such as PD and Prion diseases. ConclusionAlcohol consumption is generally considered as a harmful lifestyle habit. However, some studies have also shown a lower risk of mortality among individuals who consume low doses of alcohol (100 g/week of ethanol) or drink occasionally. Currently, one of the research focuses on alcohol consumption is whether the human body can benefit from low-dose alcohol intake. This study provides new evidence supporting a negative association between alcohol consumption and PD, and for the first time, through MR analysis, identifies the RIT2 gene as a potential mediator of the effect of alcohol consumption on PD. RIT2 is selectively expressed in the human brain. Building upon existing evidence indicating downregulated RIT2 gene expression in PD pathogenesis, our experiments confirm that low-dose alcohol consumption can upregulate RIT2 expression in the brain. In brief, alcohol consumption may suppress the pathogenesis of PD by upregulating RIT2 expression in the substantia nigra. China is facing a serious problem of population aging. This study offers important insights for long-term PD prevention and treatment strategies, with the aim of benefiting more potential PD patients through lifestyle modifications, thereby improving the quality of life of the aging population and reducing the economic burden on healthcare.

Atherosclerosis (AS) remains the core pathological basis underlying the high incidence and high rates of mortality and disability associated with cardiovascular disease (CVD) worldwide. Its essence is not merely lipid deposition, but rather an immune-mediated disease of the vascular wall characterized by an interplay of lipid metabolism disorders and chronic inflammation, with damage to vascular endothelial cells serving as the initiating event. As the disease progresses, it involves complex synergistic interactions among various cellular components, including endothelial cells, macrophages, and inflammatory cells, ultimately leading to plaque formation, instability, and even fatal thrombotic events. In recent years, the central driving role of lipid metabolic reprogramming in the progression of AS has garnered increasing attention from the scientific community. Among the vast array of lipid molecules, long-chain fatty acids (LCFAs) have become a primary focus of research due to their exceptional physiological functions. Traditional views have primarily emphasized the basic physiological functions of LCFAs: serving as highly efficient energy substrates through mitochondrial β-oxidation and acting as key structural components of cellular phospholipid membranes. However, emerging evidence clearly indicates that the functions of LCFAs extend far beyond those of mere metabolic fuel. They also act as potent bioactive signaling molecules, playing an indispensable multidimensional role in the pathogenesis of AS. Equally noteworthy and representing a paradigm shift in cardiovascular research is the emerging theory of the “gut-heart axis”. This theoretical framework views the human gut microbiota—comprising trillions of microorganisms—as a critical and metabolically active “bioreactor”. A wealth of clinical and multi-cohort epidemiological studies have conclusively demonstrated that imbalances in the composition and function of the gut microbiota are highly correlated with the clinical risk and severity of AS. Within this axis, the gut microbiota serves as the primary processing hub for dietary lipids. It actively participates in the digestion and biochemical remodeling of LCFAs, thereby altering their saturation and chemical structure and generating a wide variety of gut microbial metabolites. The effects of these gut-derived lipid metabolites extend far beyond the local intestinal microenvironment. Upon entering the bloodstream, these circulating microbiota metabolites act as endocrine signals. Given the extreme complexity of the underlying mechanisms, a comprehensive elucidation of the synergistic and bidirectional interactions between LCFAs and the gut microbiota in vascular pathology is particularly urgent. Therefore, this article aims to provide a systematic review of the multidimensional regulatory mechanisms of LCFAs and their associated gut microbiota metabolites in the onset, progression, and clinical manifestations of AS. By thoroughly exploring the interaction patterns within the “LCFAs-gut microbiota-AS” triad, this review seeks to fundamentally expand our understanding of the pathogenesis of CVDs. More importantly, translating these mechanistic insights into clinical practice holds tremendous promise. We hope to provide a solid theoretical foundation for the future development of novel AS prevention and treatment strategies based on non-traditional approaches. These include precision nutritional interventions (i.e., dietary lipid intake plans tailored to an individual’s unique microbiome profile) and targeted microbiome modulation therapies (such as next-generation probiotics, prebiotics, or specific metabolite supplements). Targeting the gut as a “reactor” to treat vascular wall lesions represents a promising direction for future cardiovascular medicine.

OBJECTIVE To develop a pharmacist-led intervention model for reducing drug-related medical insurance claim denial risks， so as to provide practical references for healthcare institutions in fulfilling their primary responsibility for medical insurance fund supervision. METHODS A risk matrix method was employed by the pharmacists to assess the risks associated with drug‑related medical insurance claim rejections in our hospital during 2024. Intervention measures were developed targeting high‑risk factors (including inappropriate indications for medical insurance coverage, exceeding the covered treatment course, and inappropriateness of gender and age) from three dimensions, namely organizational structure, technical prevention and control, and closed‑loop management. Changes in drug‑related claim rejection data were compared between 2024 (pre‑intervention) and 2025 (post‑intervention), and the interception effect of the pre‑prescription review system was evaluated after the intervention. RESULTS After the intervention, the total amount of drug‑related medical insurance claim rejections in our hospital was reduced by 57.24% compared with that before the intervention, and the number of rejected items decreased from 10 108 to 2 892. Specifically, the number of rejected items due to inappropriate indications, exceeded treatment course, inappropriate gender, and inappropriate age was reduced by 70.94%, 74.26%, 83.86%, and 96.70%, respectively. Throughout the year following the intervention, a total of 5.605 yuan million in outpatient prescription drug amounts and 4.683 million yuan in inpatient medication order amounts that did not meet the insurance‑limited payment requirements were intercepted by the pre‑prescription review system. The proportion of drug‑related claim rejection amount to the total medical service claim rejection amount of our hospital decreased to 19.7%. CONCLUSIONS The pharmacist-led multi-department collaborative， technical prevention and control， and dynamic optimization integrated full-process intervention model is highly operable and has significant practical effects. It has important promotion value in reducing drug-related medical insurance claim denial risks.

The mental health management of laboratory animals is a critical factor in ensuring the reliability of scientific research data. However, due to the subtle nature of mental state alterations and the limitations of current assessment methods, the mental health of laboratory animals is often overlooked by researchers. Therefore, there is an urgent need to explore a new, objective, simple, and practical method for evaluating mental health. Stress, as a primary factor inducing alterations in the mental state of animals, can influence experimental results across multiple research fields through the neuroendocrine-immune network. This paper first elucidates the necessity of mental health management in laboratory animals from three perspectives: factors contributing to stress, neural mechanisms of stress, and research areas affected by stress. It highlights that excluding animals with abnormal mental states before experiments can enhance the efficiency and reproducibility of biomedical studies. Second, this paper briefly summarizes existing methods for assessing the health of laboratory animals, pointing out that approaches such as behavioral tests and metabolomics have many limitations in evaluating stress responses. Existing methods struggle to meet the demand for simple, objective, and non-invasive assessment methods in animal management. Therefore, this paper focuses on hair, a biological sample with the advantages of cumulative information and non-invasive collection, and systematically describes the theoretical basis and technological advances in using hair characteristics as indicators of stress responses from three perspectives: hair traits, the levels of substances in hair, and artificial intelligence (AI). It proposes and supports an innovative technical pathway that combines hair traits with AI-based image analysis, with the aim of offering an improved solution for non-invasive and objective stress assessment, while providing theoretical support for improving the health management system of laboratory animals.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， to identify the in vivo and in vitro chemical components of total phenolic acids in Gei Herba（TPAGH）， and to clarify the pharmacological effects and potential mechanisms of the effective part in promoting acute wound healing and inhibiting scar formation. MethodsUPLC-Q-Orbitrap-MS was used to identify the chemical components of TPAGH and ingredients absorbed in vivo after topical administration. A total of 120 ICR mice were randomly divided into the model group， recombinant human epidermal growth factor（rhEGF） group（4 mg·kg^-1）， and low， medium， and high dose groups of TPAGH（3.5， 7， 14 mg·kg^-1）， with 24 mice in each group. A full-thickness skin excision model was constructed， and each administration group was coated with the drug at the wound site， and the model group was treated with an equal volume of normal saline， the treatment was continued for 30 days， during which 8 mice from each group were sacrificed on days 6， 12， and 30. The healing of the wounds in the mice was observed， and histopathological changes in the skin tissues were dynamically observed by hematoxylin-eosin（HE）， Masson， and Sirius red staining， and enzyme-linked immunosorbent assay（ELISA） was used to dynamically measure the contents of interleukin-6（IL-6）， tumor necrosis factor-α（TNF-α）， vascular endothelial growth factor A（VEGFA）， matrix metalloproteinase（MMP）-3 and MMP-9 in skin tissues. Network pharmacology was used to predict the targets related to the promotion of acute wound healing and the inhibition of scar formation by TPAGH， and molecular docking of key components and targets was performed. Gene Ontology（GO） biological process analysis and Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis were carried out for the related targets， so as to construct a network diagram of herbal material-compound-target-pathway-pharmacological effect-disease for further exploring its potential mechanisms. ResultsA total of 146 compounds were identified in TPAGH， including 28 phenylpropanoids， 31 tannins， 23 triterpenes， 49 flavonoids， and 15 others， and 16 prototype components were found in the serum of mice. Pharmacodynamic results showed that， compared with the model group， the TPAGH groups showed a significant increase in relative wound healing rate and relative scar inhibition rate（P<0.05）， and the number of new capillaries， number of fibroblasts， number of new skin appendages， epidermal regeneration rate， collagen deposition ratio， and Ⅲ/Ⅰ collagen ratio in the tissue were significantly improved（P<0.05， 0.01）， the levels of IL-6， TNF-α， MMP-3 and MMP-9 in the skin tissues were reduced to different degrees， while the level of VEGFA was increased. Network pharmacology analysis screened 10 core targets， including tumor protein 53（TP53）， sarcoma receptor coactivator（SRC）， protein kinase B（Akt）1， signal transducer and activator of transcription 3（STAT3）， epidermal growth factor receptor（EGFR） and so on， participating in 75 signaling pathways such as advanced glycation end-products（AGE）-receptor for AGE（AGE/RAGE） signaling pathway， phosphatidylinositol 3-kinase（PI3K）/Akt signaling pathway， mitogen-activated protein kinase（MAPK） signaling pathway. Molecular docking confirmed that the key components genistein， geraniin， and casuariin had good binding ability to TP53， SRC， Akt1， STAT3 and EGFR. ConclusionThis study comprehensively reflects the chemical composition of TPAGH and the absorbed components after topical administration through UPLC-Q-Orbitrap-MS. TPAGH significantly regulates key indicators of skin healing and tissue reconstruction， thereby clarifying its role in promoting acute wound healing and inhibiting scar formation. By combining in vitro and in vivo component identification with network pharmacology， the study explores how key components may bind to targets such as TP53， Akt1 and EGFR， exerting therapeutic effects through related pathways such as immune inflammation and vascular regeneration.

ObjectiveTo investigate the effect of folic acid-modified crebanine polyethylene glycol-polylactic acid hydroxyacetic acid copolymer（PEG-PLGA） nanoparticles（FA-Cre@PEG-PLGA NPs， hereinafter referred to as NPs） combined with ultrasonic irradiation on subcutaneous tumor of liver cancer in Kunming（KM） mice. MethodsEighty-four healthy male KM mice were utilized to establish a subcutaneous tumor model of mouse hepatocellular carcinoma with H22 cells， then mice were randomly divided into model group， placebo group， hydroxycamptothecin group（8 mg∙kg^-1）， low， medium and high dose crebanine raw material groups（2， 2.5， 3 mg∙kg^-1， hereinafter referred to as the low， medium and high dose crebanine groups， respectively）， low， medium and high dose NPs groups（2， 2.5， 3 mg∙kg^-1）， and low， medium and high dose NPs combined with ultrasonic irradiation groups（2， 2.5， 3 mg∙kg^-1， hereinafter referred to as the low， medium and high dose combination groups， respectively）. The corresponding doses of drugs were administered via tail vein injection， the model group received no treatment， while the placebo group was injected with an equivalent amount of normal saline. Dosing was conducted for a total of 10 times on alternate days. The body mass of the mice was monitored， and parameters such as body mass change rate， thymus index， spleen index， tumor volume， tumor weight， relative tumor growth rate（T/C）， and tumor inhibition rate（TGI） were calculated. Pathological changes in liver and kidney tissues as well as the tumor were observed by hematoxylin-eosin（HE） staining. Additionally， the levels of aspartate aminotransferase（AST）， alanine aminotransferase（ALT）， blood urea nitrogen（BUN） and creatinine（CREA） in serum of mice were detected by biochemical method. Furthermore， the effect of ultrasound on the distribution of NPs in subcutaneous tumors of mouse hepatocellular carcinoma was observed by in vivo imaging technique. ResultsAmong different treatment methods， the combination of NPs and ultrasound irradiation had the best therapeutic effect. Compared with the model group， the body mass growth rates of mice in the medium and high combination groups decreased， while the thymus index and spleen index increased， but there was no statistically significant difference in serum AST， ALT， BUN and CREA levels， indicating that NPs combined with ultrasound irradiation had little effect on the normal physiological state of the body， oth groups had TGI>40% and T/C<60%， indicating a clear anti-tumor effect. Pathological analysis showed that compared with the NPs groups， the combination groups exhibited varying degrees of necrosis in tumor cells， accompanied by less damage to the liver and kidneys. In vivo imaging of small animals showed that compared with the high dose NPs group， the high dose combination group had stronger tumor targeting ability（P<0.01）. ConclusionNPs combined with ultrasonic irradiation can not only effectively targeted the drug to the tumor site， inhibit the subcutaneous tumor growth of mouse liver cancer， but also decrease damage to liver and kidney tissues.