ObjectiveTo establish a mouse model of rheumatoid arthritis with interstitial lung disease （RA-ILD） in DBA/1 mice using Porphyromonas gingivalis （Pg） infection combined with collagen-induced arthritis （CIA）， and to comprehensively evaluate pathological characteristics in joints， lungs， and serum. MethodsForty DBA/1 mice were randomly divided into four groups， i.e.， Control， Pg infection （Pg）， CIA， and Pg infection combined with CIA （Pg+CIA）， with 10 mice in each group. Arthritis clinical symptoms were evaluated by recording arthritis incidence and clinical scores. Micro-CT scanning was used to assess knee joint pathology. Histopathological changes and collagen deposition in knee joints and lung tissues were analyzed using hematoxylin-eosin （HE） and Masson staining. Immunohistochemistry was performed to detect protein expression of α-smooth muscle actin （α-SMA）， typeⅠ collagen （ColⅠ）， and fibronectin （FN） in lung tissues. Real-time quantitative polymerase chain reaction（Real-time PCR）was used to measure mRNA expression levels of α-SMA， ColⅠ， FN， tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and IL-1β in lung tissues. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of Pg， cyclic citrullinated peptide （CCP）， and immunoglobulin G （IgG）. ResultsJoint lesions： The CIA and Pg+CIA groups showed 100% arthritis incidence， with evident joint redness， swelling， and deformity. The number of affected limbs was 27 and 28， and clinical scores were 68 and 70， respectively. No obvious clinical symptoms were observed in the Pg group. Histopathological and imaging analyses showed severe joint lesions in the CIA and Pg+CIA groups， with significantly increased histopathological scores， bone mineral density， bone volume fraction， trabecular thickness， and trabecular number compared to the Control group （P<0.01）. No obvious joint pathology was observed in the Pg group. Lung lesions： The Pg+CIA group exhibited marked alveolar inflammation， interstitial inflammatory cell infiltration， and alveolar wall thickening， with pronounced blue staining of collagen fibers. Histopathological scores and collagen area ratios were significantly higher than those of the Control， Pg， and CIA groups （P<0.05）. Lung protein and mRNA expression levels of α-SMA， ColⅠ， and FN were markedly increased， and mRNA levels of IL-6， TNF-α， and IL-1β were significantly elevated compared to the Control group （P<0.05）. Serology： The Pg+CIA group showed significantly higher levels of CCP， Pg， and IgG compared with the Control， Pg， and CIA groups （P<0.05）. ConclusionDBA/1 mice subjected to Pg infection combined with CIA exhibited pronounced symptoms and pathological features of RA-ILD， along with elevated serum anti-CCP antibody levels. This model represents a novel RA-ILD mouse model， providing a valuable experimental tool for investigating RA-ILD pathogenesis and developing new therapeutics， and serves as a basis for establishing anti-cyclic citrullinated peptide antibody （ACPA）-positive RA-ILD animal models.

ObjectiveTo develop a novel clinical predictive model for metabolic dysfunction-associated fatty liver disease （MAFLD） based on metabolic markers and anthropometric indicators， and to provide a more effective tool for the early screening and intervention of MAFLD. MethodsA retrospective analysis was performed for 2 824 individuals who underwent abdominal color Doppler ultrasound at Health Examination Center of The First Hospital of Lanzhou University from January 1， 2024 to January 1， 2025， and at a ratio of 7∶3， they were randomly divided into training set with 1 976 patients and validation set with 848 patients. Clinical data， serological markers， and abdominal ultrasound results were collected from all patients， and triglyceride-glucose （TyG） index， triglyceride-to-high-density lipoprotein cholesterol （TG/HDL-C） ratio， and anthropometric indicators were calculated. The independent samples t-test was used for comparison of normally distributed or approximately normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of continuous data with skewed distribution between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. The multivariate logistic regression analysis was used to identify independent predictive factors for MAFLD and intermediate- to high-risk MAFLD. Five risk prediction models were established for MAFLD based on the independent influencing factors， and a nomogram was plotted. The receiver operating characteristic （ROC） curve was plotted to assess model performance， and the area under the ROC curve （AUC） was calculated. The calibration curve was used to evaluate the predictive accuracy of the models， and decision curve analysis was used to assess the clinical practicability of the models. These models were then compared with traditional models. ResultsAmong the 1 976 individuals in the training set， 937 （47.42%） were diagnosed with MAFLD， and 423 （21.41%） were diagnosed with intermediate- to high-risk MAFLD； among the 848 individuals in the validation set， 406 （47.88%） were diagnosed with MAFLD. The multivariate logistic regression analysis showed that male sex （odds ratio ［OR］=0.23， 95% confidence interval ［CI］： 0.13 — 0.39， P<0.05）， waist circumference （OR=1.11， 95%CI： 1.06 — 1.17， P<0.05）， alanine aminotransferase （ALT） >40 U/L （OR=2.24， 95%CI： 1.44 — 3.51， P<0.05）， high-density lipoprotein cholesterol （HDL-C） （OR=0.07， 95%CI： 0.04 — 0.15， P<0.05）， TyG index （OR=8.27， 95%CI： 5.09 — 13.44， P<0.05）， TG/HDL-C ratio （OR=0.84， 95%CI： 0.71 — 0.99， P<0.05）， A Body Shape Index （ABSI） （OR=0.45， 95%CI： 0.39 — 0.52， P<0.05）， and body roundness index （BRI） （OR=2.31， 95%CI： 1.50 — 3.55， P<0.05） were independent influencing factors for MAFLD， and male sex （OR=0.17， 95%CI： 0.10 — 0.31， P<0.05）， age （OR=1.09， 95%CI： 1.07 — 1.11， P<0.05）， hemoglobin （OR=0.98， 95%CI： 0.97 — 0.98， P<0.05）， platelet count （OR=0.81， 95%CI： 0.70 — 0.93， P<0.05）， fasting blood glucose （OR=0.80， 95%CI： 0.71 — 0.89， P<0.05）， triglycerides （OR=0.14， 95%CI： 0.07 — 0.29， P<0.05）， TG/HDL-C ratio （OR=0.78， 95%CI： 0.67 — 0.91， P<0.05）， TyG index （OR=5.26， 95%CI： 3.32 — 8.33）， waist circumference （OR=2.50， 95%CI： 1.72 — 3.61， P<0.05）， ABSI （OR=0.58， 95%CI： 0.51 — 0.66， P<0.05）， and BRI （OR=0.01， 95%CI： 0.00 — 0.21， P<0.05） were independent influencing factors for intermediate- to high-risk MAFLD. Among the five models established， model 5 （incorporating sex， ALT elevation， HDL-C， TyG index， TG/HDL-C ratio， waist circumference， and ABSI） had the best performance， with an AUC of 0.917 （95%CI： 0.905 — 0.929） in the training set and 0.911 （95%CI： 0.892 — 0.930） in the validation set. The calibration curve showed that model 5 had good predictive accuracy， and the decision curve analysis confirmed its clinical practicability. ConclusionThe predictive model for MAFLD constructed based on metabolic markers and anthropometric indicators has good discriminatory ability and can be used to assess the risk of MAFLD. In addition， this study shows that waist circumference， TyG index， TG/HDL-C ratio， ABSI， and BRI are independently associated with intermediate- to high-risk MAFLD， but further studies are needed to confirm their value in predicting liver fibrosis progression.

Background: Rheumatoid arthritis (RA) is a systemic inflammatory disease primarily affecting the joints of the limbs. As the disease progresses, it can involve multiple organ systems. Interstitial lung disease (ILD) is the most common pulmonary manifestation of RA. Reported animal models of RA-ILD include adjuvant-induced arthritis (AA), collagen-induced arthritis (CIA), and transgenic mouse arthritis. However, the establishment criteria and evaluation methods for these models lack uniform standards, and they fail to fully replicate the clinicopathological characteristics of RA-ILD. This limitation significantly hinders research into the pathogenesis and development of therapeutic drugs for RA-ILD. Objective: The aim of the study was to review literature in China and abroad on RA-ILD animal models, analyze current research progress, identify existing issues, and propose research recommendations. Methods: Literature searches were conducted using the English keywords “rheumatoid arthritis, interstitial lung disease, model” and the Chinese keywords “(rheumatoid arthritis), (interstitial lung disease), (model)” or “(rheumatoid arthritis), (lung interstitial lesions), (model).” The search was performed in PubMed, Web of Science, CNKI, Wanfang Data, and VIP (China Science and Technology Journal Database) for articles published before November 2024. A total of 41 articles were included. Results and conclusions: The CIA model and the CIA model combined with bleomycin are commonly used due to their similarities to the histopathology and disease manifestations of human RA-ILD. Additionally, these models have appropriate cost and modeling duration, along with a high success rate, making them preferable choices. Transgenic animal models exhibit pathological features similar to the nonspecific interstitial pneumonia subtype of human RA-ILD and are useful for studying the genetic effects on RA-ILD. However, they have drawbacks such as high economic costs, long modeling durations, and a low success rate in some cases. The AA model is easy to establish, requires a short modeling period, and has low experimental costs. However, it lacks the chronic pathological development characteristic of human RA and exhibits a degree of self-limitation in lesion progression. Among other models, the comprehensive HLA-DQ8 transgenic mouse model can be used to study the combined effects of genetic and environmental factors on RA-ILD. The collagen autoantibody-induced arthritis model combined with bleomycin has a short modeling period, but it does not align well with the disease course of RA-ILD. These established animal models provide valuable insights into the pathogenesis of RA-ILD, the identification of novel biomarkers, and the development of new therapeutic approaches. Future research should focus on identifying an animal model that better replicates the physiological and pathological changes of clinical RA-ILD while being more convenient, cost-effective, and comprehensive in reflecting disease progression.

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

OBJECTIVE To provide references for pharmaceutical care in the anti-infective treatment of disseminated Talaromyces marneffei （TM）osteomyelitis complicated with pulmonary tuberculosis in a human immunodeficiency virus （HIV）-negative patient. METHODS Clinical pharmacists participated in the entire treatment process of a HIV-negative patient with disseminated TM osteomyelitis complicated by pulmonary tuberculosis. The pharmacist assisted the clinician in formulating an individualized treatment plan and improving the diagnosis based on the patient’s clinical symptoms， signs， laboratory tests， and imaging findings. Recommendations included the use of amphotericin B cholesteryl sulfate complex for antifungal therapy， the completion of a tuberculin skin test and sputum acid-fast bacilli test. The pharmacist monitored the patient’s clinical manifestations and laboratory results in real time. Upon timely detection of hypokalemia in the patient， after analyzing the causes， oral and then intravenous potassium supplementation was sequentially recommended， along with adjustments to the treatment plan （switching to itraconazole and combining it with a four-drug antituberculosis regimen of isoniazid+rifampicin+pyrazinamide+ethambutol）. Meanwhile， monitoring of itraconazole blood concentration was also advised. Additionally， the clinical pharmacist closely monitored the patient’s medication adherence and provided medication education. RESULTS The clinicians accepted the clinical pharmacist’s recommendations. The patient improved after treatment and was discharged. One-year follow-up showed that the patient was cured without adverse reactions. CONCLUSIONS Amphotericin B cholesteryl sulfate complex is an effective therapeutic agent for disseminated TM osteomyelitis in HIV-negative patients. Prolonging the course of treatment can prevent recurrence. During therapy， clinical pharmacists should strengthen pharmaceutical care as well as provide medication and health education to ensure patient safety.

Objective To analyze the differences in distribution of traditional Chinese medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without, and to explore the potential correlation between the distribution of TCM syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of TCM syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between TCM syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary TCM syndrome elements related to disease location were the lung and liver, and the primary TCM syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary TCM syndrome elements related to disease location were the lung and spleen, and the primary TCM syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of TCM syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there was significant difference in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, the results showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of TCM syndrome elements and the species abundance and composition of salivary microbiota between the patients with pulmonary nodules and the healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

ObjectiveTo unveil the mechanism of Jianpi Huogu prescription （JPHGP） in ameliorating the dyslipidemia of steroid-induced osteonecrosis of the femur head （SONFH） by oxylipidomics combined with transcriptomics. MethodsSixty SD rats were assigned into normal， model， low-， medium-， and high-dose （2.5， 5， 10 g·kg^-1， respectively） JPHGP， and Jiangushengwan （1.53 g·kg^-1） groups. Lipopolysaccharide was injected into the tail vein at a dose of 20 μg·kg^-1 on days 1 and 2， and methylprednisolone sodium succinate was injected at a dose of 40 mg·kg^-1 into the buttock muscle on days 3 to 5. The normal group received an equal volume of normal saline. Drug administration by gavage began 4 weeks after the last injection， and samples were taken after administration for 8 weeks. Hematoxylin-eosin staining was conducted to reveal the histopathological changes of the femoral head， and the number of adipocytes， the rate of empty bone lacunae， and the trabecular area were calculated. Micro-computed tomography was used for revealing the histological and histomorphometrical changes of the femoral head. Enzyme-linked immunosorbent assay was employed to measure the serum levels of triglyceride （TG）， total cholesterol （TC）， low-density lipoprotein （LDL）， high-density lipoprotein （HDL）， apolipoprotein A1 （ApoA1）， and apolipoprotein B （ApoB）. At the same time， the femoral head was collected for oxylipidomic and transcriptomic detection. The differential metabolites and differential genes were enriched and analyzed， and the target genes regulating lipid metabolism were predicted. The predicted target proteins were further verified by molecular docking， immunohistochemistry， and Western blot. ResultsCompared with the normal group， the model group showcased thinning of the femoral head， trabecular fracture， karyopyknosis， subchondral cystic degeneration， increases in the number of adipocytes and the rate of empty bone lacunae （P<0.01）， a reduction in the trabecular area （P<0.01）， decreases in BMD， Tb.Th， Tb.N， and BV/TV， and increases in Tb.Sp and BS/BV （P<0.01）. Compared with the model group， the JPHGP groups showed no obvious thinning of the femoral head or subchondroidal cystic degeneration. The high- and medium-dose JPHGP groups presented declines in the number of adipocytes and the rate of empty bone lacunae， an increase in the trabecular area （P<0.05， P<0.01）， rises in BMD， Tb.Th， Tb.N， and BV/TV， and decreases in Tb.Sp and BS/BV （P<0.05， P<0.01）. Compared with the normal group， the model group showcased raised serum levels of TG， TC， LDL， and ApoB and lowered serum levels of HDL and ApoA1 （P<0.01）. Compared with the model group， the JPHGP groups had lowered serum levels of TG， TC， LDL， and ApoB （P<0.05， P<0.01） and a risen serum level of ApoA1 （P<0.05， P<0.01）. Moreover， the serum level of HDL in the high-dose JPHGP group increased （P<0.01）. A total of 19 different metabolites of disease set and drug set were screened out by oxylipidomics of the femoral head， and 119 core genes with restored expression were detected by transcriptomics. The enriched pathways were mainly concentrated in inflammation， lipids， apoptosis， and osteoclast differentiation. Molecular docking， immunohistochemistry， and Western blot results showed that compared with the normal group， the model group displayed increased content of 5-lipoxygenase （5-LO） and peroxisome proliferator-activated receptor γ （PPARγ） in the femoral head （P<0.01）. Compared with the model group， medium- and high-dose JPHGP reduced the content of 5-LO and PPARγ （P<0.05， P<0.01）. ConclusionJPHGP can restore the levels of oxidized lipid metabolites by regulating the 5-LO-PPARγ axis to treat SONFH in rats. Relevant studies provide experimental evidence for the efficacy mechanism of JPHGP in the treatment of SONFH.

ObjectiveTo unveil the mechanism of Jianpi Huogu prescription （JPHGP） in ameliorating the dyslipidemia of steroid-induced osteonecrosis of the femur head （SONFH） by oxylipidomics combined with transcriptomics. MethodsSixty SD rats were assigned into normal， model， low-， medium-， and high-dose （2.5， 5， 10 g·kg^-1， respectively） JPHGP， and Jiangushengwan （1.53 g·kg^-1） groups. Lipopolysaccharide was injected into the tail vein at a dose of 20 μg·kg^-1 on days 1 and 2， and methylprednisolone sodium succinate was injected at a dose of 40 mg·kg^-1 into the buttock muscle on days 3 to 5. The normal group received an equal volume of normal saline. Drug administration by gavage began 4 weeks after the last injection， and samples were taken after administration for 8 weeks. Hematoxylin-eosin staining was conducted to reveal the histopathological changes of the femoral head， and the number of adipocytes， the rate of empty bone lacunae， and the trabecular area were calculated. Micro-computed tomography was used for revealing the histological and histomorphometrical changes of the femoral head. Enzyme-linked immunosorbent assay was employed to measure the serum levels of triglyceride （TG）， total cholesterol （TC）， low-density lipoprotein （LDL）， high-density lipoprotein （HDL）， apolipoprotein A1 （ApoA1）， and apolipoprotein B （ApoB）. At the same time， the femoral head was collected for oxylipidomic and transcriptomic detection. The differential metabolites and differential genes were enriched and analyzed， and the target genes regulating lipid metabolism were predicted. The predicted target proteins were further verified by molecular docking， immunohistochemistry， and Western blot. ResultsCompared with the normal group， the model group showcased thinning of the femoral head， trabecular fracture， karyopyknosis， subchondral cystic degeneration， increases in the number of adipocytes and the rate of empty bone lacunae （P<0.01）， a reduction in the trabecular area （P<0.01）， decreases in BMD， Tb.Th， Tb.N， and BV/TV， and increases in Tb.Sp and BS/BV （P<0.01）. Compared with the model group， the JPHGP groups showed no obvious thinning of the femoral head or subchondroidal cystic degeneration. The high- and medium-dose JPHGP groups presented declines in the number of adipocytes and the rate of empty bone lacunae， an increase in the trabecular area （P<0.05， P<0.01）， rises in BMD， Tb.Th， Tb.N， and BV/TV， and decreases in Tb.Sp and BS/BV （P<0.05， P<0.01）. Compared with the normal group， the model group showcased raised serum levels of TG， TC， LDL， and ApoB and lowered serum levels of HDL and ApoA1 （P<0.01）. Compared with the model group， the JPHGP groups had lowered serum levels of TG， TC， LDL， and ApoB （P<0.05， P<0.01） and a risen serum level of ApoA1 （P<0.05， P<0.01）. Moreover， the serum level of HDL in the high-dose JPHGP group increased （P<0.01）. A total of 19 different metabolites of disease set and drug set were screened out by oxylipidomics of the femoral head， and 119 core genes with restored expression were detected by transcriptomics. The enriched pathways were mainly concentrated in inflammation， lipids， apoptosis， and osteoclast differentiation. Molecular docking， immunohistochemistry， and Western blot results showed that compared with the normal group， the model group displayed increased content of 5-lipoxygenase （5-LO） and peroxisome proliferator-activated receptor γ （PPARγ） in the femoral head （P<0.01）. Compared with the model group， medium- and high-dose JPHGP reduced the content of 5-LO and PPARγ （P<0.05， P<0.01）. ConclusionJPHGP can restore the levels of oxidized lipid metabolites by regulating the 5-LO-PPARγ axis to treat SONFH in rats. Relevant studies provide experimental evidence for the efficacy mechanism of JPHGP in the treatment of SONFH.

To summarize the nursing experience of a patient with coronary heart disease who was left in the radial artery during the removal of the radial artery sheath after coronary angiography via the radial artery pathway.Nursing points:to start the emergency transfer process,to shorten the treatment transfer time;to assist to locate the position of the sheath to provide a basis for the selection of surgical incision;to conduct dynamic assessment of hemostatic effect,prevention of radial artery occlusion;to closely monitor pain and signs to prevent vasovagal reflex;to implement the whole psychological intervention,and to reduce the psychological burden of patients and their families.The ruptured sheath tube was successfully removed by emergency surgery of vascular surgery.A total of 6 days after the operation,the patient was transferred to cardiac surgery for coronary artery bypass grafting,and was discharged 23 days later.After 3 months of follow-up,the blood supply of the limbs was good,and the incision healed well.