ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.

ObjectiveThrough qualitatively and quantitatively analysis of the differences in chemical composition between the combined decoction and single decoction of Huaganjian and comparison of their core efficacy， to explore the rationality of the flexible clinical application of Huaganjian compound preparations and single-flavored dispensing granules. MethodsUltra performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Exactive Orbitrap MS） was used to qualitatively analyze the combined decoction and single decoction samples of Huaganjian， and meanwhile， the contents of four index components（geniposide， paeoniflorin， hesperidin and paeonol） were quantitatively analyzed by high performance liquid chromatography（HPLC）. Nonalcoholic fatty liver disease（NAFLD） rat model induced by high-fat diet was applied to compare the efficacy of combined decoction and single decoction of Huaganjian. A total of 30 male SD rats were randomly divided into the control group， model group， lovastatin group（1.8 mg·kg^-1）， combined decoction group（1.26 g·kg^-1） and single decoction group（1.18 g·kg^-1）. After successful modeling， lovastatin group， combined decoction group and single decoction group were given corresponding doses of drugs by intragastric administration every day， and the control group and model group were given equal amounts of normal saline by intragastric administration， after 4 weeks of administration， the serum and liver tissues were collected， and the contents of alanine aminotransferase（ALT）， aspartate aminotransferase（AST）， total cholesterol（TC）， triglyceride（TG）， low-density lipoprotein cholesterol（LDL-C） and high-density lipoprotein cholesterol（HDL-C） in serum of rats were detected， and the liver pathological examination was carried out by hematoxylin-eosin（HE） staining and oil red O staining， so as to compare differences of their efficacy. ResultsSeventy chemical components were initially identified and attributed from the lyophilized powder of the combined decoction and single decoction samples of Huaganjian， and there was no obvious difference in composition between the two. Further quantitative analysis showed that the contents of geniposide， paeoniflorin， hesperidin and paeonol in the combined decoction samples were significantly increased when compared with those of the single decoction samples（P<0.01）. The pharmacodynamic results showed that compared with the model group， both the combined and single decoction groups of Huaganjian could improve the liver index of NAFLD rats， reduce the serum levels of AST， ALT， TC， TG and LDL-C， increase the serum level of HDL-C， and ameliorate the pathological changes of liver cell steatosis and fat accumulation. However， there was no significant difference in pharmacodynamic effects between the combined decoction group and the single decoction group. ConclusionThere is no significant difference between the combined decoction and single decoction of Huaganjian in terms of chemical composition， but the contents of the four index components show significantly difference. Both of them can significantly improve the fat accumulation and liver function in NAFLD rats. This study provides a reference basis for the rational clinical application and evaluation of famous classical formula compound preparations and single-flavored dispensing granules.

This study aims to explore the protective effect of Chaihu Jia Longgu Muli Decoction on rats with heart failure after myocardial infarction, and to clarify its possible mechanisms, providing a new basis for basic research on the mechanism of classic Chinese medicinal formula-mediated inflammatory response in preventing and treating heart failure induced by apoptosis after myocardial infarction. A heart failure model after myocardial infarction was established in rats by coronary artery ligation. The rats were divided into sham group, model group, and low, medium, and high-dose groups of Chaihu Jia Longgu Muli Decoction, with 10 rats in each group. The low-dose, medium-dose, and high-dose groups of Chaihu Jia Longgu Muli Decoction were given 6.3, 12.6, and 25.2 g·kg~(-1) doses by gavage, respectively. The sham group and model group were given an equal volume of distilled water by gavage once daily for four consecutive weeks. Cardiac function was assessed using color Doppler echocardiography. Myocardial pathology was detected by hematoxylin-eosin(HE) staining, apoptosis was measured by TUNEL assay, and mitophagy was observed by transmission electron microscopy. The levels of tumor necrosis factor-α(TNF-α), interleukin(IL)-1β, and N-terminal pro-B-type natriuretic peptide(NT-proBNP) in serum were detected by enzyme-linked immunosorbent assay(ELISA). The expression of apoptosis-related proteins B-cell lymphoma 2(Bcl-2), Bcl-2-associated X protein(Bax), and cleaved caspase-3 was detected by Western blot. Additionally, the expression of phosphorylated nuclear transcription factor-κB(NF-κB) p65(p-NF-κB p65)(upstream) and nuclear factor kappa B inhibitor alpha(IκBα)(downstream) in the NF-κB signaling pathway was assessed by Western blot. The results showed that compared with the sham group, left ventricular ejection fraction(LVEF) and left ventricular short axis shortening(LVFS) in the model group were significantly reduced, while left ventricular end diastolic diameter(LVEDD) and left ventricular end systolic diameter(LVESD) increased significantly. Myocardial tissue damage was severe, with widened intercellular spaces and disorganized cell arrangement. The apoptosis rate was increased, and mitochondria were enlarged with increased vacuoles. Levels of TNF-α, IL-1β, and NT-proBNP were elevated, indicating an obvious inflammatory response. The expression of pro-apoptotic factors Bax and cleaved caspase-3 increased, while the anti-apoptotic factor Bcl-2 decreased. The expression of p-NF-κB p65 was upregulated, and the expression of IκBα was downregulated. In contrast, the Chaihu Jia Longgu Muli Decoction groups showed significantly improved of LVEF, LVFS and decreased LVEDD, LVESD compared to the model group. Myocardial tissue damage was alleviated, and intercellular spaces were reduced. The apoptosis rate decreased, mitochondrial volume decreased, and the levels of TNF-α, IL-1β, and NT-proBNP were lower. The expression of pro-apoptotic factors Bax and cleaved caspase-3 decreased, while the expression of the anti-apoptotic factor Bcl-2 increased. Additionally, the expression of p-NF-κB p65 decreased, while IκBα expression increased. In summary, this experimental study shows that Chaihu Jia Longgu Muli Decoction can reduce the inflammatory response and apoptosis rate in rats with heart failure after myocardial infarction, which may be related to the regulation of the IκBα/NF-κB signaling pathway.
Animals ; Apoptosis/drug effects* ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Myocardial Infarction/physiopathology* ; Male ; NF-kappa B/genetics* ; Heart Failure/etiology* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; NF-KappaB Inhibitor alpha/genetics* ; Humans ; Tumor Necrosis Factor-alpha/genetics*

OBJECTIVE: To assess the cardioprotective effect and impact of Qishen Granules (QSG) on different ischemic areas of the myocardium in heart failure (HF) rats by evaluating its metabolic pattern, substrate utilization, and mechanistic modulation. METHODS: In vivo, echocardiography and histology were used to assess rat cardiac function; positron emission tomography was performed to assess the abundance of glucose metabolism in the ischemic border and remote areas of the heart; fatty acid metabolism and ATP production levels were assessed by hematologic and biochemical analyses. The above experiments evaluated the cardioprotective effect of QSG on left anterior descending ligation-induced HF in rats and the mode of energy metabolism modulation. In vitro, a hypoxia-induced H9C2 model was established, mitochondrial damage was evaluated by flow cytometry, and nuclear translocation of hypoxia-inducible factor-1 α (HIF-1 α) was observed by immunofluorescence to assess the mechanism of energy metabolism regulation by QSG in hypoxic and normoxia conditions. RESULTS: QSG regulated the pattern of glucose and fatty acid metabolism in the border and remote areas of the heart via the HIF-1 α pathway, and improved cardiac function in HF rats. Specifically, QSG promoted HIF-1 α expression and entry into the nucleus at high levels of hypoxia (P<0.05), thereby promoting increased compensatory glucose metabolism; while reducing nuclear accumulation of HIF-1 α at relatively low levels of hypoxia (P<0.05), promoting the increased lipid metabolism. CONCLUSIONS QSG regulates the protein stability of HIF-1 α, thereby coordinating energy supply balance between the ischemic border and remote areas of the myocardium. This alleviates the energy metabolism disorder caused by ischemic injury.
Animals ; Myocardial Infarction/physiopathology* ; Male ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Rats, Sprague-Dawley ; Glucose/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Energy Metabolism/drug effects* ; Rats ; Fatty Acids/metabolism* ; Myocardium/pathology*

Objective:To investigate the effect of different timing of arterial -venous extracorporeal membrane oxygenation (VA-ECMO) on the prognosis of patients with acute myocardial infarction complicated with cardiogenic shock (AMICS).Methods:This study was a prospective cohort study. AMICS patients received VA-ECMO support primary percutaneous coronary intervention in Henan Provincial People's Hospital from May 2017 to July 2023 were divided into early VA-ECMO group and late VA-ECMO group. 64 AMICS patients who met the indications for VA-ECMO implantation, but did not revive VA-ECMO were included as control group. Demographic characteristics, coronary interventional (PCI) information and complications after VA-ECMO implantation were collected. The primary end points was 1-year survival, minor end point were in-hospital and perioperative death. Multivariate Logistic and Cox regression models were used to evaluate the effect of timing of VA-ECMO on prognosis of AMICS patients. Kaplan-Meier survival curve was used to analyze the 1-year survival outcome of the 3 groups.Results:A total of 143 AMICS patients were included, and materials of 136 patients entered in the final analysis, including 42 in the early VA-ECMO group, 34 in the late VA-ECMO group, and 60 in the non-VA-ECMO group. Compared with the late VA-ECMO group, the early VA-ECMO group had a higher ratio of PPCI after VA-ECMO, a longer D-to-B time, a shorter VA-ECMO support time, a higher success rate of VA-ECMO withdrawal, and a lower complication rate (all P<0.05). Compared with the early VA-ECMO group, the perioperative, in-hospital and 1-year mortality were significantly higher in Non-ECMO support (all P<0.05). There was no difference in perioperative and in-hospital mortality between the early VA-ECMO group and the late VA-ECMO group, but the 1-year mortality in the late VA-ECMO group was significantly higher ( P<0.05). Perioperative, in-hospital and 1-year mortality rates were lower in the late VA-ECMO group than in the no-VA-ECMO group, but the differences were not statistically significant. Multivariate Logistic and Cox regression analysis showed that after adjusting interference factors, early VA-ECMO was still a protective factor for in-hospital ( OR=0.244, P=0.015) and one year ( HR=0.308, P=0.001)mortality. Kaplan-Merier survival curve showed that compared with the late VA-ECMO group and the group without VA-ECMO, the early VA-ECMO group had the highest 1-year survival rate. Conclusion:Patients with AMICS may benefit more from early VA-ECMO than from late VA-ECMO support for PPCI.

Purpose::Vibrio vulnificus ( V. Vulnificus) infection is characterized by rapid onset, aggressive progression, and challenging treatment. Bacterial resistance poses a significant challenge for clinical anti-infection treatment and is thus the subject of research. Enhancing host infection tolerance represents a novel infection prevention strategy to improve patient survival. Our team initially identified cytochrome P4501A1 (CYP1A1) as an important target owing to its negative modulation of the body's infection tolerance. This study explored the superior effects of the CYP1A1 inhibitor bergamottin compared to antibiotic combination therapy on the survival of mice infected with multidrug-resistant V. Vulnificus and the protection of their vital organs. Methods::An increasing concentration gradient method was used to induce multidrug-resistant V. Vulnificus development. We established a lethal infection model in C57BL/6J male mice and evaluated the effect of bergamottin on mouse survival. A mild infection model was established in C57BL/6J male mice, and the serum levels of creatinine, urea nitrogen, aspartate aminotransferase, and alanine aminotransferase were determined using enzyme-linked immunosorbent assay to evaluate the effect of bergamottin on liver and kidney function. The morphological changes induced in the presence of bergamottin in mouse organs were evaluated by hematoxylin and eosin staining of liver and kidney tissues. The bacterial growth curve and organ load determination were used to evaluate whether bergamottin has a direct antibacterial effect on multidrug-resistant V. Vulnificus. Quantification of inflammatory factors in serum by enzyme-linked immunosorbent assay and the expression levels of inflammatory factors in liver and kidney tissues by real-time quantitative polymerase chain reaction were performed to evaluate the effect of bergamottin on inflammatory factor levels. Western blot analysis of IκBα, phosphorylated IκBα, p65, and phosphorylated p65 protein expression in liver and kidney tissues and in human hepatocellular carcinomas-2 and human kidney-2 cell lines was used to evaluate the effect of bergamottin on the nuclear factor kappa-B signaling pathway. One-way ANOVA and Kaplan-Meier analysis were used for statistical analysis. Results::In mice infected with multidrug-resistant V. Vulnificus, bergamottin prolonged survival ( p = 0.014), reduced the serum creatinine ( p = 0.002), urea nitrogen ( p = 0.030), aspartate aminotransferase ( p = 0.029), and alanine aminotransferase ( p = 0.003) levels, and protected the cellular morphology of liver and kidney tissues. Bergamottin inhibited interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α expression in serum (IL-1β: p = 0.010, IL-6: p = 0.029, TNF-α: p = 0.025) and inhibited the protein expression of the inflammatory factors IL-1β, IL-6, TNF-α in liver (IL-1β: p = 0.010, IL-6: p = 0.011, TNF-α: p = 0.037) and kidney (IL-1β: p = 0.016, IL-6: p = 0.011, TNF-α: p = 0.008) tissues. Bergamottin did not affect the proliferation of multidrug-resistant V. Vulnificus or the bacterial load in the mouse peritoneal lavage fluid ( p = 0.225), liver ( p = 0.186), or kidney ( p = 0.637). Conclusion::Bergamottin enhances the tolerance of mice to multidrug-resistant V. Vulnificus infection. This study can serve as a reference and guide the development of novel clinical treatment strategies for V. Vulnificus.

Objective To develop a GIS-based 3D playback system for the flight human-plane data to realize the fusion of pilots'airborne flight data and physiological data.Methods The 3D playback system was developed with the Browser/Server(B/S)architecture,micro-server model,Java language and Spring Cloud technology framework,which was composed of three functional modules for flight process reproduction,physiological situational awareness and critical event calibration analysis.Results The system developed achieved time synchronization and data fusion of airborne flight data and physiological data with a time synchronization frequency of 1 Hz and a refresh rate of not less than 120 frames/s.Conclusion The system developed with high safety,stability,reliability and accuracy facilitates pilot in-flight physiological monitoring and fusion and simultaneous display of airborne flight data and physiological data,which can be used as an important platform for decision-making support in flight training.[Chinese Medical Equipment Journal,2024,45(10):14-19]

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

Objective:To establish an ultrasound radiomics model by integrating clinical, pathological, and conventional ultrasound features with radiomics characteristics, and to explore its clinical value in predicting endocrine resistance in hormone receptor(HR)-positive breast cancer.Methods:A retrospective analysis was performed on 478 patients with HR-positive breast cancer from January 2017 to December 2021 in the Second Affiliated Hospital of Harbin Medical University, of which 430 were resistant and 48 were sensitive. The clinical, pathological and immunohistochemical data and ultrasound images were collected.Firstly, the propensity score was used to process and match the data. Secondly, Logistic regression was used to screen clinical, pathological, and conventional ultrasound features associated with endocrine resistance. Then, PyRadiomics was used to extract the radiomic features of grayscale ultrasound images, and a series of methods such as Lasso regression were used to screen the radiomic features related to endocrine resistance. Seven machine learning methods such as random forest were used to build a radiomics model. Finally, clinical, pathological and ultrasound features were added to establish a clinical pathological model, a clinical pathological ultrasound model, a clinical pathological radiomics model and a combined model of the four features, and the model effectiveness was evaluated.Results:①Propensity score matching: 96 patients were matched, including 48 patients in the drug-resistant group and 48 patients in the sensitive group. ②Screening clinical pathological conventional ultrasound features related to endocrine resistance: lymph node metastasis, tumor diameter, posterior echo attenuation, and growth orientation were independent predictors of endocrine resistance (all P<0.05). ③Screening radiomics features related to endocrine resistance: 18 features such as Dependence Entropy. ④Establishing radiomics model: the machine learning model of random forest method (AUC=0.80) performed best. ⑤Radiomics model integrating clinical, pathological and conventional ultrasound features: the AUC of the clinical pathological model was 0.70, the AUC of the clinical pathological ultrasound model was 0.78, the AUC of the clinical pathological radiomics model was 0.82, and the AUC of the combined model was 0.86. Conclusions:The radiomics model established by the random forest method performs best in predicting endocrine resistance in HR-positive breast cancer. The model that integrates multiple features performs best in assessing endocrine resistance.which is expected to provide an objective basis for clinicians to predict endocrine resistance in HR-positive breast cancer.