The efficacy mechanism of the alcoholic extract of Gnaphalium affine was investigated by observing its influence on oxidative stress and intestinal flora in rats modeled for chronic obstructive pulmonary disease(COPD). UPLC-MS was used to evaluate the quality of the alcoholic extract of G. affine, and 72 rats were randomly divided into six groups, with COPD models established in five groups by cigarette smoke combined with airway drip lipopolysaccharide, and the rats were given the positive drug of Danlong Oral Solution, as well as low-, medium-, and high-doses alcoholic extract of G. affine, respectively. After two weeks of continuous gastric gavage, the body weights and general morphology observations were performed; HE staining and Masson staining were used to verify the effects of the alcoholic extract of G. affine on alveolar inflammation and collagen deposition area in COPD rats; the oxidative stress indexes CAT and GSH in serum and SOD and MDA in lung tissue of the rats were measured, and the mRNA expression of HO-1, Nrf2, and NQO1 were determined by qRT-PCR. The protein expressions of HO-1, Nrf2, and NQO1 were determined by the Western blot method, and the mechanism by which the alcoholic extract of G. affine affected oxidative stress in COPD rats was explored. Finally, the influence of G. affine on the changes in intestinal flora caused by COPD was studied by 16S rRNA sequencing. The results showed that a total of 121 chemical components were identified by UPLC-MS, including 70 positive and 51 negative ion modes. In animal experiments, it was found that the alcoholic extracts of G. affine were able to reduce the percentage of collagen deposition, affect the oxidative stress indexes such as CAT, GSH, SOD, MDA, as well as the mRNA and protein expression of Nrf2, HO-1, and NQO1. The 16S rRNA sequencing results showed an increase in the level of Lactobacillales and a decrease in the level of Desulfovibrio and Desulfovibrionales, suggesting that the alcoholic extracts of G. affine could reverse the changes in intestinal flora caused by COPD. In conclusion, the alcoholic extracts of G. affine may exert anti-COPD effects by affecting the oxidative stress pathway and modulating the changes in intestinal flora.
Animals ; Oxidative Stress/drug effects* ; Pulmonary Disease, Chronic Obstructive/genetics* ; Rats ; Male ; Gastrointestinal Microbiome/drug effects* ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/administration & dosage* ; NF-E2-Related Factor 2/metabolism* ; Humans ; Lung/metabolism*

OBJECTIVE: To evaluate the clinical effect and safety of acupuncture manipulation on treatment of intractable facial paralysis (IFP), and verify the practicality and precision of the Anzhong Facial Paralysis Precision Scale (Eyelid Closure Grading Scale, AFPPS-ECGS). METHODS: A multicentre, single-blind, randomized controlled trial was conducted from October 2022 to June 2024. Eighty-nine IFP participants were randomly assigned to an ordinary acupuncture group (OAG, 45 cases) and a characteristic acupuncture group (CAG, 44 cases) using a random number table method. The main acupoints selected included Yangbai (GB 14), Quanliao (SI 18), Yingxiang (LI 20), Shuigou (GV 26), Dicang (ST 4), Chengjiang (CV 24), Taiyang (EX-HN 5), Jiache (ST 6), Fengchi (GB 20), and Hegu (LI 4). The OAG patients received ordinary acupuncture manipulation, while the CAG received characteristic acupuncture manipulation. Both groups received acupuncture treatment 3 times a week, with 10 times per course, lasting for 10 weeks. Facial recovery was assessed at baseline and after the 1st, 2nd and 3rd treatment course by AFPPS-ECGS and the House-Brackmann (H-B) Grading Scale. Infrared thermography technology was used to observe the temperature difference between healthy and affected sides in various facial regions. Adverse events and laboratory test abnormalities were recorded. The correlation between the scores of the two scales was analyzed using Pearson correlation coefficient. RESULTS: After the 2nd treatment course, the two groups showed statistically significant differences in AFPPS-ECGS scores (P<0.05), with even greater significance after the 3rd course (P<0.01). Similarly, H-B Grading Scale scores demonstrated significant differences between groups following the 3rd treatment course (P<0.05). Regarding temperature measurements, significant differences in temperatures of frontal and ocular areas were observed after the 2nd course (P<0.05), becoming more pronounced after the 3rd course (P<0.01). Additionally, mouth corner temperature differences reached statistical significance by the 3rd course (P<0.05). No safety-related incidents were observed during the study. Correlation analysis revealed that the AFPPS-ECGS and the H-B Grading Scale were strongly correlated (r=0.86, 0.91, 0.93, and 0.91 at baseline, and after 1st, 2nd, and 3rd treatment course, respectively, all P<0.01). CONCLUSIONS Acupuncture is an effective treatment for IFP, and the characteristic acupuncture manipulation enhances the therapeutic effect. The use of the AFPPS-ECGS can more accurately reflect the recovery status of patients with IFP. (Trial registration No. ChiCTR2200065442).
Humans ; Acupuncture Therapy/methods* ; Facial Paralysis/therapy* ; Female ; Male ; Middle Aged ; Adult ; Treatment Outcome ; Acupuncture Points ; Aged

Objective:To explore the application value of different nutritional screening tools in the evaluation of preoperative malnutrition assessment of Crohn's patients. Methods:Using the convenient sampling method, a retrospective analysis was conducted on CD patients who underwent elective surgery at the general surgery department of General Hospital of Eastern Theater Command from January 2021 to March 2022. The preoperative nutritional status of the patients was understood. Taking the consensus on malnutrition assessment diagnosis standards (GLIM) as the gold standard. The correlation, difference and diagnostic efficacy of 3 nutritional risk screening tools were compared. Results:A total of 212 patients were included. Using GLIM as the diagnostic standard, 131 patients (61.79％) had malnutrition. The incidence of malnutrition risk was 66.03％, 85.38％ and 55.66％ using NRS 2002 score, NS IBD score and PNI score, respectively. The sensitivities of the above three scores in the preoperative nutritional screening of IBD patients were 81.46％, 85.48％, 79.63％, respectively; the specificity were 62.36％, 54.71％, 57.12％, respectively; and the areas under the curve were 0.749, 0.763, 0.831, respectively. In the evaluation of diagnostic efficacy, NS IBD score had the highest sensitivity, and NRS 2002 had the best specificity. Conclusion:For patients with Crohn's disease undergoing elective surgery, the three nutritional risk screening tools can provide a basis for malnutrition risk screening. The items of PNI score are objective, concise, and convenient. As for the evaluation of diagnostic efficacy, the NS IBD score has the highest sensitivity and the NRS 2002 has the best specificity.

Objective:To investigate the status quo of training and domestic use of 707 clinical nutrition support specialty nurses from 21 provinces,cities,and autonomous regions in China. And to analyze their influencing factors and provide reference for improving the training system of clinical nutrition support specialty nurses,selection and development of specialist nurses in clinical nutrition support. Methods:From October to November 2023,a cross-sectional survey was conducted on 707 clinical nutrition support specialty nurses from 21 provinces,cities,and autonomous regions across China was conducted using a convenience sampling method based on a questionnaire about the training and home use of clinical nutrition support nurses. Univariate and multiple linear regression analysis was used to examine the use status and application of clinical nutrition support specialty nurses in five aspects:clinical nursing practice,nursing education,nursing management,coordination,nursing research and consultation. Results:The use of specialist clinical nutrition support nurses is not ideal,with 75.67％ of specialist nurses scoring less than 208 points (i.e. less than 80％ of the total score). Among the use of different dimensions,the clinical nursing practice dimension received the highest score (54.17±10.26),followed by the nursing education dimension (36.98±8.00). The results of multiple linear regression analysis show that hospital level and professional title are independent influencing factors influencing the use and development of specialist nurses. Conclusion:There is a need to further improve the utilisation of clinical nutrition support nurses. It is recommended that links and cooperation between hospitals at all levels,communities,and families be strengthened. For specialist nurses with higher professional titles,encourage them to fully play their roles,strengthen training in weak areas,continuously optimize the professional ability of clinical nutrition support nursing teams,comprehensively improve the quality of clinical nutrition support specialist nursing,and promote their high-level development.

Objective:To investigate the relationship between phase angle (PA) and nutritional status,duration of mechanical ventilation,length of intensive care unit (ICU) stay,and clinical outcomes in patients with severe acute pancreatitis (SAP) complicated with ARDS. Methods:The clinical data of patients with SAP complicated with ARDS admitted to the surgical ICU,Jinling hospital,medical school of Nanjing University,from July 2023 to March 2024 were retrospectively collected. Patients are divided into low-PA group and normal-PA group based on phase angle. The correlation analysis between phase angle,nutritional status,and clinical outcomes,and evaluation of risk factors for mortality in patients with SAP combined with ARDS were performed. Result:A total of 83 patients with SAP complicated with ARDS were included in this study. PA was negatively correlated with nutritional risk scores (rs=-0.352,P=0.001),duration of mechanical ventilation (rp=-0.475,P<0.001),length of ICU stay (rp=-0.313,P=0.004),and mortality (rs=-0.371,P=0.001). Univariate analysis showed statistically significant differences in age,PA value,and duration of mechanical ventilation for predicting mortality (P<0.05);Multivariate analysis showed that the PA value was an independent risk factor for mortality (P<0.05). Conclusion:PA is significantly correlated with clinical outcomes,such as nutritional risk,duration of mechanical ventilation,length of ICU stay and mortality,and may be a promising biomarker in future.

Objective:To summarize the best evidence on case management of patients with home enteral nutrition.Methods:Relevant evidence on the case management of home enteral nutrition patients was retrieved by literature search,and the evidence was extracted and summarized for the literature that met the quality requirements.Result:A total of 10 literatures were included,including 1 guideline,3 expert consensus,2 industry standards,1 systematic review and 3 randomized controlled trials.By establishment of archives,policy management,establishment of multidisciplinary teams,overall evaluation of home enteral nutrition,as well as implementation management,a total of 33 home enteral nutrition case management was summarized from 6 aspects including health education and follow-up,etc.Conclusion:All the summarized relevant evidence about case filing and management of home enteral nutrition patients can be applied in clinical practice to promote the standardized management of home enteral nutrition.

Background::Thoracic aortic aneurysm (TAA) is a fatal cardiovascular disease, the pathogenesis of which has not yet been clarified. This study aimed to identify and validate the diagnostic markers of TAA to provide a strong theoretical basis for developing new methods to prevent and treat this disease.Methods::Gene expression profiles of the GSE9106, GSE26155, and GSE155468 datasets were acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the "limma" package in R. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), random forest, and binary logistic regression analyses were used to screen the diagnostic marker genes. Single-sample gene set enrichment analysis (ssGSEA) was used to estimate immune cell infiltration in TAA.Results::A total of 16 DEGs were identified. The enrichment and functional correlation analyses showed that DEGs were mainly associated with inflammatory response pathways and collagen-related diseases. Collagen type I alpha 1 chain ( COL1A1) and synaptotagmin like 2 ( SYTL2) were identified as diagnostic marker genes with a high diagnostic value for TAA. The expression of COL1A1 and SYTL2 was considerably higher in TAA vascular wall tissues than in the corresponding normal tissues, and there were significant differences in the infiltration of immune cells between TAA and normal vascular wall tissues. Additionally, COL1A1 and SYTL2 expression were associated with the infiltration of immune cells in the vascular wall tissue. Single-cell analysis showed that COL1A1 in TAA was mainly derived from fibroblasts and SYTL2 mainly from cluster of differentiation (CD)8 + T cells. In addition, single-cell analysis indicated that fibroblasts and CD8 + T cells in TAA were significantly higher than those in normal arterial wall tissue. Conclusions::COL1A1 and SYTL2 may serve as diagnostic marker genes for TAA. The upregulation of SYTL2 and COL1A1 may be involved in the inflammatory infiltration of the vessel wall and poor extracellular matrix remodeling, promoting the progression of TAA.

Objective To explore the prediction of hospital indoor microbial concentration in air based on real-time indoor air environment monitoring data and machine learning algorithms.Methods Four locations in a hospital were selected as monitoring sampling points from May 23 to June 5,2022.The"internet of things"sensor was used to monitor a variety of real-time air environment data.Air microbial concentration data collected at each point were matched,and the gradient boosting decision tree(GBDT)was used to predict real-time indoor microbial concentra-tion in air.Five other common machine learning models were selected for comparison,including random forest(RF),decision tree(DT),k-nearest neighbor(KNN),linear regression(LR)and artificial neural network(ANN).The validity of the model was verified by the mean absolute error(MAE),root mean square error(RMSE)and mean absolute percentage error(MAPE).Results The MAPE value of GBDT model in the outpa-tient elevator room(point A),bronchoscopy room(point B),CT waiting area(point C),and nurses'station in the supply room(point D)were 22.49％,36.28％,29.34％,and 26.43％,respectively.The mean performance of the GBDT model was higher than that of other machine learning models at three sampling points and slightly lower than that of the ANN model at only one sampling point.The mean MAPE value of GBDT model at four sampling points was 28.64％,that is,the predicted value deviated from the actual value by 28.64％,indicating that GBDT model has good prediction results and the predicted value was within the available range.Conclusion The GBDT machine learning model based on real-time indoor air environment monitoring data can improve the prediction accuracy of in-door air microbial concentration in hospitals.

This study aims to establish a rapid and non-destructive method for recognizing the origins and cultivation patterns of Astragali Radix. A hyperspectral imaging system(spectral ranges: 400-1 000 nm, 900-1 700 nm; detection time: 15 s) was used to examine the samples of Astragali Radix with different origins and cultivation patterns. The collected hyperspectral datasets were highly correlated and numerous, which required the establishment of stable and reliable dimension reduction and classification models. Firstly, the original spectra were preprocessed by normalization, Gaussian smoothing, and masking. Then, principal component analysis(PCA), partial least squares-discriminant analysis(PLS-DA), and competitive adaptive reweighted sampling(CARS) were performed to reduce the dimension of the hyperspectral data. Finally, support vector machine(SVM), feedforward neural network(FFNN), and convolutional neural network(CNN) were used for data training of the spectral images and spectral curves with dimension reduction. The results showed that applying CARS as a variable selection method before PLS-DA on the hyperspectral data of Astragali Radix achieved the accuracy, precision, and recall of 100% on the CNN test dataset. The F_1-score and area under the curve of ROC(AUC) reached 1. This method is convenient, quick, sample-saving, and non-destructive, providing technical support for rapid identification of the origins and cultivation patterns of Astragali Radix.
Drugs, Chinese Herbal/chemistry* ; Neural Networks, Computer ; Algorithms ; Support Vector Machine ; Principal Component Analysis ; Discriminant Analysis ; Hyperspectral Imaging/methods* ; Least-Squares Analysis ; Astragalus Plant/growth & development* ; Astragalus propinquus/growth & development*