Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Aim To explore the mechanism of Jiawei Shaofu Zhuyu decoction in antagonizing endometriosis fibrosis by regulating mitophagy.Methods After the animal model was constructed,the syndrome was evalu-ated by general condition,organ water content and ther-mal imaging.The curative effect was evaluated by the weight of ectopic focus and the degree of adhesion.The pathological changes were compared using HE stai-ning,transmission electron microscopy,Masson and Sir-ius red staining.The expression of PINK1 and Parkin was detected by immunohistochemistry.The expression of mRNA and protein was determined by qPCR and Western blot,and the level of serum ROS was detected by ELISA.Results The autonomic activity of model mice was weakened,the water content of organs rose,and the temperature of limbs and lower abdomen was reduced by thermal imaging.HE staining showed obvi-ous hyperplasia of ectopic epithelium and glands.Transmission electron microscopy showed mitochondrial and endoplasmic reticulum structure damage,and nor-mal autophagy structure disappeared.Masson and Siri-us red staining showed increased collagen deposition;immunohistochemistry showed decreased expression of PINK1 and Parkin in ectopic foci.qPCR and Western blot showed that the expression of PINK1,Parkin,Bec-lin1,LC3 mRNA and protein in ectopic foci of model mice decreased,the expression of p62 mRNA and pro-tein increased,and serum ROS increased.The syn-drome performance of model mice was improved after the intervention of Jiawei Shaofu Zhuyu decoction;the inflammatory infiltration of ectopic foci was relieved,the morphology of mitochondria and endoplasmic retic-ulum was restored,and normal autophagy structure ap-peared.The degree of collagen deposition and fibrosis was reduced;the mRNA and protein expression of PINK1,Parkin,Beclin1 and LC3 increased.The ex-pression of p62 mRNA and protein decreased,and the level of ROS decreased.Conclusions Jiawei Shaofu Zhuyu decoction can improve the fibrosis of ectopic le-sions in mice with endometriosis of cold-dampness sta-sis syndrome,which may be related to the regulation of mitophagy.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Aim To explore the mechanism of Jiawei Shaofu Zhuyu decoction in antagonizing endometriosis fibrosis by regulating mitophagy.Methods After the animal model was constructed,the syndrome was evalu-ated by general condition,organ water content and ther-mal imaging.The curative effect was evaluated by the weight of ectopic focus and the degree of adhesion.The pathological changes were compared using HE stai-ning,transmission electron microscopy,Masson and Sir-ius red staining.The expression of PINK1 and Parkin was detected by immunohistochemistry.The expression of mRNA and protein was determined by qPCR and Western blot,and the level of serum ROS was detected by ELISA.Results The autonomic activity of model mice was weakened,the water content of organs rose,and the temperature of limbs and lower abdomen was reduced by thermal imaging.HE staining showed obvi-ous hyperplasia of ectopic epithelium and glands.Transmission electron microscopy showed mitochondrial and endoplasmic reticulum structure damage,and nor-mal autophagy structure disappeared.Masson and Siri-us red staining showed increased collagen deposition;immunohistochemistry showed decreased expression of PINK1 and Parkin in ectopic foci.qPCR and Western blot showed that the expression of PINK1,Parkin,Bec-lin1,LC3 mRNA and protein in ectopic foci of model mice decreased,the expression of p62 mRNA and pro-tein increased,and serum ROS increased.The syn-drome performance of model mice was improved after the intervention of Jiawei Shaofu Zhuyu decoction;the inflammatory infiltration of ectopic foci was relieved,the morphology of mitochondria and endoplasmic retic-ulum was restored,and normal autophagy structure ap-peared.The degree of collagen deposition and fibrosis was reduced;the mRNA and protein expression of PINK1,Parkin,Beclin1 and LC3 increased.The ex-pression of p62 mRNA and protein decreased,and the level of ROS decreased.Conclusions Jiawei Shaofu Zhuyu decoction can improve the fibrosis of ectopic le-sions in mice with endometriosis of cold-dampness sta-sis syndrome,which may be related to the regulation of mitophagy.

Aim To investigate the intervention effect of Rehmannia radix water extract on bleomycin(BLM)-induced pulmonary fibrosis in mice combined with metabolomics and to reveal the potential mechanism,in order to provide new ideas for clinical treatment of pul-monary fibrosis.Methods Male C57BL/6N mice were randomly divided into the control group,model group,pirfenidone group(positive control,PFD,270 mg·kg-1),and low dose(DH-L,4.55 g·kg-1)group,medium dose(DH-M,9.1 g·kg-1)group and high dose(DH-H,18.2 g·kg-1)group of Rehman-nia.Except for the control group,BLM(5 mg·kg-1)was instilled into the trachea to establish the model of pulmonary fibrosis in the other groups.The survival rate,lung index and blood oxygen saturation of mice in each group were evaluated.HE and Masson staining were used to observe the pathological changes of lung tissue.WBP was used to detect lung function.Flow cytometry was used to detect the apoptosis of primary lung cells,ROS and immune cells.ELISA was used to detect the levels of fibrosis markers and inflammatory factors(α-SMA,collagen Ⅰ,collagen Ⅲ,TGF-β1,TNF-α,IL-1 β,and IL-6).Biochemical method was employed to detect the contents of GSH-Px,T-SOD and MDA.Liquid chromatograph mass spectrometer(LC-MS)metabolomics was used to analyze the changes of serum metabolic profile.Results Water extract of Re-hmannia significantly increased the survival rate,oxy-gen saturation and lung function of mice with pulmona-ry fibrosis,reduced the lung coefficient,ameliorated pathological damage and collagen deposition in lung tissue,reduced the levels of apoptosis and oxidative stress,and down-regulated the levels of inflammatory factors in lung tissue.It regulated the levels of metabo-lites such as bile acid metabolism,sphingolipid metabo-lism,and unsaturated fatty acid metabolism.Conclu-sions Water extract of Rehmannia inhibits lung injury and collagen deposition in mice with pulmonary fibrosis by inhibiting inflammatory response,which may be a-chieved by regulating the levels of inflammatory factors through the metabolic pathways of bile acid and sphin-golipid.

Aim To investigate the intervention effect of Rehmannia radix water extract on bleomycin(BLM)-induced pulmonary fibrosis in mice combined with metabolomics and to reveal the potential mechanism,in order to provide new ideas for clinical treatment of pul-monary fibrosis.Methods Male C57BL/6N mice were randomly divided into the control group,model group,pirfenidone group(positive control,PFD,270 mg·kg-1),and low dose(DH-L,4.55 g·kg-1)group,medium dose(DH-M,9.1 g·kg-1)group and high dose(DH-H,18.2 g·kg-1)group of Rehman-nia.Except for the control group,BLM(5 mg·kg-1)was instilled into the trachea to establish the model of pulmonary fibrosis in the other groups.The survival rate,lung index and blood oxygen saturation of mice in each group were evaluated.HE and Masson staining were used to observe the pathological changes of lung tissue.WBP was used to detect lung function.Flow cytometry was used to detect the apoptosis of primary lung cells,ROS and immune cells.ELISA was used to detect the levels of fibrosis markers and inflammatory factors(α-SMA,collagen Ⅰ,collagen Ⅲ,TGF-β1,TNF-α,IL-1 β,and IL-6).Biochemical method was employed to detect the contents of GSH-Px,T-SOD and MDA.Liquid chromatograph mass spectrometer(LC-MS)metabolomics was used to analyze the changes of serum metabolic profile.Results Water extract of Re-hmannia significantly increased the survival rate,oxy-gen saturation and lung function of mice with pulmona-ry fibrosis,reduced the lung coefficient,ameliorated pathological damage and collagen deposition in lung tissue,reduced the levels of apoptosis and oxidative stress,and down-regulated the levels of inflammatory factors in lung tissue.It regulated the levels of metabo-lites such as bile acid metabolism,sphingolipid metabo-lism,and unsaturated fatty acid metabolism.Conclu-sions Water extract of Rehmannia inhibits lung injury and collagen deposition in mice with pulmonary fibrosis by inhibiting inflammatory response,which may be a-chieved by regulating the levels of inflammatory factors through the metabolic pathways of bile acid and sphin-golipid.

Objective To systematically evaluate the effects of total intravenous anesthesia and inhalational anesthesia on postoperative recovery in patients undergoing transsphenoidal pituitary tumor resection.Methods A comprehensive search was conducted in international biomedical databases including Ovid Medline,Embase,CINAHL(EBSCO),Cochrane Library,and Web of Science,from inception to July 4,2023.Additionally,ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform were searched for ongoing and completed trials.The randomized controlled trials(RCT)comparing total intravenous anesthesia and inhalational anesthesia in patients undergoing transsphenoidal surgery for pituitary tumors were included.The methodological quality of the included studies was evaluated by the Cochrane Collaboration tool.Relevant data were extracted and synthesized for analysis.Results A total of 327 records were identified,of which eight RCTs met the inclusion criteria.Four studies showed that the patients receiving desflurane or sevoflurane anesthesia experienced faster emergence from anesthesia than those receiving propofol.Two studies indicated that patients in the propofol group had lower levels of emergence agitation and a lower incidence of early postoperative nausea and vomiting.The results on postoperative cognitive function were inconsistent across studies.No differences were found between the groups in terms of postoperative complications or overall recovery quality during hospitalization.Conclusions Inhalational anesthesia appears to provide an advantage in promoting faster emergence following transsphenoidal pituitary surgery,whereas total intravenous anesthesia may contribute to smoother and more stable recovery.Further high-quality studies are needed to clarify the effects of different anesthetic techniques on both short- and long-term postoperative recovery.
Humans ; Anesthesia, Intravenous ; Pituitary Neoplasms/surgery* ; Anesthesia, Inhalation ; Randomized Controlled Trials as Topic ; Anesthesia Recovery Period ; Pituitary Gland/surgery* ; Postoperative Period

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

Objective To investigate the postoperative efficacy of laparoscopic hiatal hernia repair(LHHR)combined with Toupet or Dor fundoplication for the treatment of esophageal hiatal hernia(HH).Methods A retrospective analysis was conducted on the case data of HH patients who underwent LHHR combined with Toupet(Toupet group,n=53)and Dor(Dor group,n=53)fundoplication between December 2018 and December 2022 in Department of General Surgery of Gansu Provincial Hospital.Intraoperative and postoperative recovery outcomes of both groups were observed.We analyzed and compared the incidence of dysphagia and gastroesophageal reflux disease questionnaire(GERD-Q)scores at preoperative and postoperative intervals of 1 month,6 months,and 1 year.The incidence of postoperative complications and the 1-year recurrence rate were compared between the two groups.Additionally,factors influencing postoperative dysphagia within the first month were examined.Results The differences between the two groups in operation time,intraoperative bleeding,postoperative ventilation time,postoperative extubation time and hospitalization time were not statistically significant(P>0.05).There was no significant difference in the incidence of immediate postoperative dysphagia in two groups(P>0.05).Furthermore,the differences between the two groups in the incidence of postoperative complications,such as bloating,abdominal pain and diarrhea,were not statistically significant(P>0.05).The incidence of dysphagia in Toupet group was higher than that in Dor group at 1 month postoperatively,and the difference was statistically significant(P=0.017);but the difference in the incidence of dysphagia between the two groups at 6 months and 1 year postoperatively was not statistically significant(P=0.767,1.000).The results of binary logistic regression analysis showed that both surgical procedure(OR=2.613,95%CI 1.141-5.983,P=0.023)and esophageal contractile reserve function(OR=2.921,95%CI 1.203-7.095,P=0.018)were independent risk factors for the incidence of dysphagia in patients with HH at 1 month after surgery.Compared with the preoperative period,the GERD-Q symptom scores were lower in both groups at 1 month,6 months,and 1 year postoperatively,and the difference was statistically significant(P<0.05);but there was no statistically significant difference between the groups at the same time point(Fintergroup=0.334,P=0.565).The difference between the two groups in 1-year postoperative recurrence rates was not statistically significant(P>0.05).Conclusions LHHR combined with Toupet or Dor fundoplication are both safe and effective surgical procedures for the treatment of HH,with excellent reflux control,fewer complications and lower recurrence rates,but Toupet fundoplication is more likely to have postoperative short-term dysphagia than Dor fundoplication.