Due to its synergistic effects and reduced side effects, combination therapy has become an important strategy for treating complex diseases. In traditional Chinese medicine (TCM), the "monarch, minister, assistant, envoy" compatibilities theory provides a systematic framework for drug compatibility and has guided the formation of a large number of classic formulas. However, due to the complex compositions and diverse mechanisms of action of TCM, it is difficult to comprehensively reveal its potential synergistic patterns using traditional methods. Synergistic prediction based on molecular compatibility theory provides new ideas for identifying combinations of active compounds in TCM. Compared to resource-intensive traditional experimental methods, artificial intelligence possesses the ability to mine synergistic patterns from multi-omics and structural data, providing an efficient means for modeling and optimizing TCM combinations. This paper systematically reviews the application progress of AI in the synergistic prediction of TCM active compounds and explores the challenges and prospects of its application in modeling combination relationships, thereby contributing to the modernization of TCM theory and methodological innovation.
Artificial Intelligence ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/pharmacology* ; Humans ; Drug Synergism

Objective To explore the mechanism of action of Neiyi Soft Extract in the treatment of endometriosis(EMS)based on network pharmacology and transcriptomics.Methods A model of SD rat with EMS was replicated by autotransplantation method.After successful modeling,the rats were randomly divided into model group,Neiyi Soft Extract low-,medium-and high-dose groups and dienogest group,with 10 rats in each group.Another sham-operated group(10 rats)was set up.After four consecutive weeks of intervention,the volume size of the endometriotic lesions was measured,and its pathological changes were detected by hematoxylin-eosin(HE)staining.RNA was extracted from the rat lesions for transcriptomic sequencing,and Gene Ontology(GO)enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)functional enrichment analysis were performed on the differential genes among various groups.The main active ingredients and their targets of Neiyi Soft Extract were collected and screened in databases such as TCMSP,the disease targets of EMS were collected through databases such as OMIM,the intersection targets between the drug ingredient targets and the diseases were obtained by using Venn diagrams,GO enrichment analysis and KEGG pathway enrichment analysis of genes in the intersection targets of the drug ingredients and the diseases were performed by using gene enrichment analysis online tool(Metascape).The network pharmacology enrichment pathway and transcriptomics enrichment pathway were taken for intersection,the mRNA and protein expression levels of the key targets on the intersection pathway were correspondingly detected by real-time quantitative polymerase chain reaction(qPCR)and Western Blot,respectively.Results The volume of lesions in the model group was significantly increased compared with that of the sham-operated group(P<0.01);the volume of lesions in rats in the drug-administered groups was significantly reduced compared with that of the model group(P<0.05).A total of 341 active ingredients were obtained from Neiyi Soft Extract,and there were 2 178 disease-related targets of EMS,and 278 intersections between drug targets and disease targets;189 differential genes were screened in the sham-operated group and the model group;255 differential genes were screened in the model group and Neiyi Soft Extract high-dose group;and 740 differential genes were screened in the sham-operated group and the Neiyi Soft Extract high-dose group,including 390 up-regulated genes and 350 down-regulated genes.The result of intersection of KEGG enrichment pathways between the network pharmacology and transcriptomics showed that the distriution mainly included P53 signaling pathway,FOXO signaling pathway,cell cycle,etc.The qPCR and Western Blot validation results showed that Neiyi Soft Extract could inhibit the proliferation of endometrial stromal cells and up-regulated the mRNA and protein expression levels of BAX,Caspase3 in EMS rats(P<0.05 or P<0.01),and down-regulated BCL-2 mRNA and protein expression levels(P<0.05 or P<0.01).Conclusion Neiyi Soft Extract may play a therapeutic role in the treatment of EMS by regulating the P53 signaling pathway.

Curettage is the main treatment method for oral maxillofacial cystic lesions,but simple curettage may easily damage surrounding structures such as adjacent teeth and nerves,leading to incomplete removal of the cyst and large jaw defects.The curettage assisted by endoscopy can provide a good surgical field for the surgeons,can clearly identify the important anatomical structure during the operation and can remove the cyst wall tissue as much as possible,thereby reducing the damage and reducing the recurrence rate of the lesion.This article combines the characteristics of maxillofacial surgery with clinical treatment experience,summarizes relevant literature from both domestic and international sources,and engages in discussions with experts in order to provide reference for the clinical treatment of jaw cystic lesions with endo-scope assisted curettage.

Due to the high complexity and subject variability of motor imagery electroencephalogram, its decoding is limited by the inadequate accuracy of traditional recognition models. To resolve this problem, a recognition model for motor imagery electroencephalogram based on flicker noise spectrum (FNS) and weighted filter bank common spatial pattern ( wFBCSP) was proposed. First, the FNS method was used to analyze the motor imagery electroencephalogram. Using the second derivative moment as structure function, the ensued precursor time series were generated by using a sliding window strategy, so that hidden dynamic information of transition phase could be captured. Then, based on the characteristic of signal frequency band, the feature of the transition phase precursor time series and reaction phase series were extracted by wFBCSP, generating features representing relevant transition and reaction phase. To make the selected features adapt to subject variability and realize better generalization, algorithm of minimum redundancy maximum relevance was further used to select features. Finally, support vector machine as the classifier was used for the classification. In the motor imagery electroencephalogram recognition, the method proposed in this study yielded an average accuracy of 86.34%, which is higher than the comparison methods. Thus, our proposed method provides a new idea for decoding motor imagery electroencephalogram.
Brain-Computer Interfaces ; Imagination ; Signal Processing, Computer-Assisted ; Electroencephalography/methods* ; Algorithms ; Spectrum Analysis

Aiming at the problem of low recognition accuracy of motor imagery electroencephalogram signal due to individual differences of subjects, an individual adaptive feature representation method of motor imagery electroencephalogram signal is proposed in this paper. Firstly, based on the individual differences and signal characteristics in different frequency bands, an adaptive channel selection method based on expansive relevant features with label F (ReliefF) was proposed. By extracting five time-frequency domain observation features of each frequency band signal, ReliefF algorithm was employed to evaluate the effectiveness of the frequency band signal in each channel, and then the corresponding signal channel was selected for each frequency band. Secondly, a feature representation method of common space pattern (CSP) based on fast correlation-based filter (FCBF) was proposed (CSP-FCBF). The features of electroencephalogram signal were extracted by CSP, and the best feature sets were obtained by using FCBF to optimize the features, so as to realize the effective state representation of motor imagery electroencephalogram signal. Finally, support vector machine (SVM) was adopted as a classifier to realize identification. Experimental results show that the proposed method in this research can effectively represent the states of motor imagery electroencephalogram signal, with an average identification accuracy of (83.0±5.5)% for four types of states, which is 6.6% higher than the traditional CSP feature representation method. The research results obtained in the feature representation of motor imagery electroencephalogram signal lay the foundation for the realization of adaptive electroencephalogram signal decoding and its application.
Humans ; Imagination ; Signal Processing, Computer-Assisted ; Brain-Computer Interfaces ; Electroencephalography/methods* ; Imagery, Psychotherapy ; Algorithms

Objective:To explore the normal ranges of perfusion parameters between cerebral hemisphere, cerebellar hemisphere and brain anatomical subregions (56 pairs) in different gender and age groups with multiple post labeling delay time (Multi-PLD) arterial spin labeling (ASL) imaging.Methods:From November 2020 to December 2020, 42 healthy adult volunteers (Male 25, Female 17) were recruited to perform 7 PLD ASL imaging, including 21 young adults (15 males and 6 females, aged 23—35 years) and 21 seniors (10 males and 11 females, aged 36—74 years). The data was processed offline by Cereflow software to obtain arterial arrival time (ATT) and corrected cerebral blood flow (CBF) and cerebral blood volume (CBV) perfusion parameters. SimpleITK standardization function was used to standardize the calculated perfusion image according to the anatomical automatic labeling (AAL) template. Therefore, CBF, ATT, CBV perfusion values of brain subregions were obtained. Paired samples t test, Wilcoxon rank sum test, independent samples t test and Mann-Whitney U test were used to compare the differences of perfusion parameters in the cerebral hemisphere, the cerebellar hemisphere, brain subregions depending on side, gender and age. Pearson correlation analysis was used to compare the correlations of perfusion parameters with age. Results:CBF in 62.5% (35/56) subregions and CBV in 44.6% (25/56) subregions were higher in right side than those in left side. ATT in most brain anatomical subregions (16/56) were higher in left side. The CBF [(35.30±8.31) vs. (34.34±7.53) ml·100g -1·min -1, P=0.021], CBV [(0.47±0.11) vs. (0.45±0.09) ml/100g, P<0.001], ATT [(1.30±0.10) vs. (1.24±0.11) s, P<0.001] in left cerebellar hemisphere were higher than that of right side. The CBF (28/56) of cerebral hemisphere, cerebellar hemisphere and brain subregions was higher in females than that in males, while ATT in 83.9% (47/56) subregions was lower than that in males (all P<0.05). CBV in female subjects was higher only in 5 brain regions (superior occipital gyrus, middle occipital gyrus, inferior occipital gyrus, superior parietal gyrus and cerebelum_7b) (all P<0.05). In young subjects, CBF in 44.6% (25/56) subregions and CBV in 33.9% (19/56) subregions were higher than those in the senior group (all P<0.05). The ATT in most subregions in young group were lower than those in senior group, but the difference was statistically significant only in rectus gyrus ( P=0.026) and paracentral lobule ( P=0.006). The CBF ( r=-0.430, P=0.005) and CBV ( r=-0.327, P=0.035) of cerebral hemisphere were negatively correlated with age. The CBF (24/25, r range:-0.497 —-0.343, all P<0.05) and CBV (16/19, r range:-0.474 —-0.322, all P<0.05) in most subregions were negatively correlated with age, while ATT was positively correlated (gyrus rectus: r=0.311, P=0.045; paracentral lobule: r=0.392, P=0.010). Conclusions:Multi-PLD ASL imaging could be applied for quantitative analysis of brain perfusion. The perfusion parameters of anatomical subregions are different depending on side, gender, and age.

Objective:To investigate the application value of magnetic resonance (MR) diffusion tensor imaging (DTI) automatic fiber quantification (AFQ) in the diagnosis and prediction of Alzheimer's disease (AD).Methods:Clinical and MR data of 21 patients with AD (AD group) and 33 normal controls (NC group) were collected.AFQ software was used to analyze DTI data, track 20 white matter fiber bundles in the brain, and compare the differences of fractional anisotropy (FA) and mean diffusivity (MD) value of each bundle between groups.Each fiber bundle was divided into 100 equal parts along the direction of travel, and the FA or MD value of each part was taken as a characteristic.Screening the characteristics with statistic differences between groups for classification of AD and NC by support vector machine (SVM) with leave one method for cross validation.Classification effectiveness was evaluated using the receiver operating characteristic (ROC) curve.Results:Eleven (left/right anterior thalamic radiation (ATR), left/right corticospinal tract (CST), genu of corpus callosum (CC Genu), right inferior longitudinal fasciculus (ILF), right superior longitudinal fasciculus (SLF), left/right uncinated fasciculus (UF), and left/right arcuate fasciculus (AF)) of the 20 fiber bundles were successfully tracked in all subjects.Compared with NC group, the FA values of 2 fiber bundles (left/right UF) in AD group were significantly decreased( t=-2.532, -2.391, both P<0.05), and the MD values of 7 fiber bundles (left ATR, left/right CST, right ILF, left/right UF, and left AF) were significantly increased ( t=2.569, 2.411, 2.108, 2.357, 3.773, 3.796, 3.492, all P<0.05). Among the 2 200 characteristics of 11 fiber bundles, 412 classification characteristics with inter-group differences were selected.Among which, 78 FA characteristics were distributed in 7 fiber bundles (left ATR, left/right CST, CC Genu, right ILF, left/right UF), and 334 MD characteristics were distributed in 9 fiber tracts (left/right ATR, left/right CST, CC Genu, right ILF, left/right UF, and left AF). The accuracy of SVM classification was 85.19%, sensitivity was 80.95%, specificity was 87.88%, and area under ROC curve was 0.894 7. Conclusion:AFQ analysis based on DTI has a high application value in the diagnosis and prediction of AD.

In the context of the "Belt and Road" initiative, We systematically analyzed the general education and training systems of 16 Western Pacific countries and regions, including general practitioner college education, post-graduation education, and faculty status. Developed countries and regions have a long-term medical education system, strong faculty, and a comprehensive training model for general practitioners. Underdeveloped countries and regions are relatively weak in educational institutions, faculty, and general practitioner training models. The underdeveloped countries and regions should develop a general medical education and training system in terms of strengthening the construction of general medical disciplines, strengthening the supervision and certification of general practitioners, improving the general medical training model, and strengthening the construction of teachers.

Cardiopulmonary resuscitation (CPR) training plays an important role in improving the survival rate of patients with out-of-hospital cardiac arrest, and attention should be paid to the knowledge education and skill training of CPR for the public. This article reviews the current situation of CPR training at home and abroad, and puts forward suggestions for CPR training in China, particularly emphasizes that CPR training should be included in the compulsory education and that general practitioners should play a leading role in public CPR training.

Dietary nitrate which mainly comes from green leafy vegetables, is absorbed into blood circulation by the intestinal mucosa. Parotid gland is an important organ for transporting nitrate. Nitrate in blood is taken up by sialin, a nitrate transporter and concentrated in salivary glands and secreted into saliva. The salivary nitrate is partially reduced to nitrite and nitric oxide by oral bacteria, and then salivary nitrate and nitrite return into blood circulation with swallowing and intestinal mucosal absorption. As a non-classic source of nitric oxide, nitrate-nitrite-nitric oxide pathway plays an important role on physiological and pathological conditions, especially on the condition of hypoxia and ischemia. These functions include body protection, such as gastrointestinal tract, cardiovascular system, anti-inflammation, regulation of glucose/lipid metabolism, improvement of sport ability, maintaining gut microbiome hemostasis, and alleviating senility. The traditional view on nitrate as a harmful substance to human body has been proved to be lack of scientific evidence. With further research and application, as a pioneer from the mouth to the whole body, nitrate is expected to play a crucial part in human health, and prevention and treatment of systemic diseases.