This 5-year ecological study assessed the association between meteorological factors and rhegmatogenous retinal detachment (RRD) frequency in 571 eyes of 543 cases of primary RRD at the Jikei University Kashiwa Hospital, Japan. We examined the monthly and seasonal distributions of RRD frequency using one-way analysis of variance. We then evaluated the relationship between monthly RRD frequency and 36 meteorological parameters using Poisson regression analysis. Furthermore, we developed multivariate regression models to predict the frequency of RRD based on specific meteorological parameters. There were no significant differences in the monthly and seasonal distributions . The following eight parameters were associated with a lower RRD frequency: average sea level barometric pressure and average daily variation of average temperature, maximum temperature, maximum wind speed, maximum instantaneous wind speed, humidity, average sea level barometric pressure, and minimum sea level barometric pressure (P < 0.05). The best model to predict RRD frequency showed sufficient validity  and predictive power . In conclusion, low atmospheric pressure and high meteorological stability are significantly associated with a higher frequency of RRD. In addition, the Poisson regression analysis showed sufficient validity and predictability for predicting RRD frequency. When humans see an image, the retina captures the image and converts it into signals, which are then sent to the brain2. Retinal detachment (RD) is a condition in which the retina is pulled away from its normal position and is defined as the separation of the neurosensory retina from the retinal pigment epithelium4. When RD occurs due to round holes, tears, or breaks in the retina, the RD is classified as rhegmatogenous RD (RRD)3.The retina is a thin, multi-layer tissue located at the back of the eyeball; it is composed of 10 layers from the inner limiting membrane to the retinal pigment epithelium6. The annual RRD incidence varies across different ethnicities and geographical regions, ranging from 6.3 to 18.2 cases per 100,000 persons, as reported in studies conducted in both Western and Asian countries9. An epidemiological study from Japan reported an RRD incidence of 16.5  per 100,000 persons with a mean patient age of 54.4 years10.RRD is one of the most serious and major ophthalmological diseases, which can lead to irreversible loss of vision in the absence of appropriate treatment12. Researchers have also studied the association between meteorological factors and RD frequency by analyzing its monthly and seasonal variations21. These studies have focused on identifying meteorological parameters that may have a significant effect on RD frequency22. Although several such studies have been conducted across the globe, the association between meteorological factors and RD frequency remains controversial24. Moreover, no similar studies have been conducted in Japan.Multiple factors can influence RD occurrence; these include myopia, cataract surgery, trauma, intraocular inflammation, retinal breaks, and vitreoretinal disordersHerein, we first investigated the association between meteorological factors and RD frequency in Japan. Additionally, multivariate regression models with varying numbers of meteorological parameters were developed to predict RRD frequency.This was a retrospective ecological study, approved by the Institutional Review Board of the Jikei University School of Medicine and was conducted in accordance to the principles of the Declaration of Helsinki [approval number: 32–224 (10305)]. According to the Ethical Guidelines for Medical and Health Research Involving Human Subjects , it was not necessary to get informed consent from each research subject as this study did not involve intervention and neither utilized human biological specimens nor special care-required personal information. Instead, we posted the documents approved by the Institutional Review Board of the Jikei University School of Medicine on the website and announced the information of this research on the bulletin board in our hospital. We guaranteed the subjects the right to refuse participation in this study at any time. The parents/legally authorized representatives of subjects that are under age of 20 were also guaranteed the right to refuse.We reviewed the medical records of patients who were diagnosed with primary RRD at the Department of Ophthalmology, the Jikei University Kashiwa Hospital, Kashiwa, Japan. The study period was defined as January 2015 to December 2019, using the date of surgical treatment. Since almost all patients with RRD underwent surgery in our hospital, only a few patients with RRD with no surgical history were excluded from the analysis. We also excluded patients diagnosed with secondary RRD  and those with primary RRD if an accurate day of onset (within a 1-week range) could not be determined. Patient characteristics in the medical records included age, sex, and day of RRD onset. We defined day of onset as the day when the first RRD-related symptom  appeared. Instances of recurrent RRD in the same patient were counted as additional cases.https://www.data.jma.go.jp/gmd/risk/obsdl/index.php), namely average temperature (°C), maximum temperature (℃), minimum temperature (℃), amount of precipitation (mm), duration of sunshine (h), average wind speed (m/s), maximum wind speed (m/s), and maximum instantaneous wind speed (m/s) in Abiko City, and average vapor pressure (hPa), humidity (%), average sea level barometric pressure (hPa), and minimum sea level barometric pressure (hPa) in Chiba City. These locations (Abiko and Chiba) were the nearest observation sites to Kashiwa city, for which meteorological data were available.We obtained data on 12 daily meteorological parameters from the Japan Meteorological Agency . For the analysis, a year was divided into four seasons: spring ; summer ; autumn ; and winter . Monthly and seasonal comparison of RRD frequency was performed using one-way analysis of variance with Python 3.7.6. Values of P < 0.05 were considered statistically significant.Subsequently, we predicted RRD frequency (eyes per month) from meteorological parameters with a Poisson regression model, using Python 3.7.6 and MATLAB 9.1. First, we calculated RRD frequency and average meteorological parameters for each month. In addition, we reconstituted monthly variation (MV) and average daily variation (ADV) of each month for each meteorological parameter. MV was calculated as the difference between the parameters for the current and previous months. ADV for each day was calculated as the difference between the parameters for the current and previous days. We used the absolute value to calculate variation in order to avoid canceling values. The monthly RRD frequency was used as the response variable and the average meteorological parameters with two types of variation parameters were used as the explanatory variables. We conducted a univariate analysis for each parameter pair, and those with P < 0.05 were considered statistically significant.27. For the calculation of CV-VE, the 5-year data were randomly divided into training (80%) and test (20%) data. We calculated VE by substituting test data into the model created using the training data, which was then defined as CV-VE. Furthermore, we applied the leave-one-out cross-validation method to determine the validity of each model.Lastly, we performed a multivariate analysis, using three types of multivariate regression models: Models A, B, and C; Model A included all 36 parameters as explanatory variables; Model B included parameters that were significantly correlated (P < 0.05) with RRD frequency in the univariate analysis; Model C, in which the effect of multicollinearity was excluded, did not include the significantly correlated explanatory variables from Model B if the variance inflation factor (VIF) > 5. In each model, we calculated the Akaike’s information criterion with correction for small sample size (AICc), Bayesian information criterion (BIC), proportion of variance explained (VE), and proportion of variance explained by cross-validation method (CV-VE)In total, medical records of 571 eyes in 543 primary RRD cases were obtained for the study, among which there were 185 women (34.1%) and 358 men (65.9%). The average patient age was 56.10 ± 13.67 (15–92) years. Further, 322 (56.4%) right eyes and 249 (43.6%) left eyes were included in the analysis, and there were 28 (4.9%) cases of recurrent RRD.The monthly RRD frequency (eyes per month) was highest in July n = 11.6) and the lowest in February (n = 7.8) : average sea level barometric pressure, average daily variation of average temperature, maximum temperature, maximum wind speed, maximum instantaneous wind speed, humidity, average sea level barometric pressure, and minimum sea level barometric pressure (P < 0.05) Table . In otheThree models of multivariate analyses to predict RRD frequency (eyes per month) showed that prediction accuracy improved by reducing the parameters Table . Model APredicted onsets of each model, calculated using the leave-one-out cross-validation method, were compared with observed onsets by time course Fig. . PredictIn this study, we analyzed the monthly and seasonal variations in RRD frequency as well as the association of meteorological factors and primary RRD frequency. The key findings of our study include the following: (1) no significant differences were found within monthly or seasonal variations of RRD frequency; (2) low atmospheric pressure and high stability (low ADV) of the seven meteorological parameters significantly affected the increase in RRD frequency; and (3) RRD frequency can be predicted based on specific meteorological parameters with excellent reliability and predictability using a Poisson regression model.28. Several studies from Lebanon17, Finland28, Spain21, India19, and Taiwan18 have reported a significant increase in RD frequency during warmer seasons (spring and/or summer) compared with colder seasons . In contrast, two studies from Turkey24 and Croatia23 reported no significant seasonal variations, and one study from Kuwait15 reported a significant increase in the winter. Although the underlying cause of these seasonal variations has not been elucidated, several hypotheses have been suggested. One hypothesis is that ultraviolet light, which is abundant in summer, heats the vitreous and retina, induces posterior vitreous detachment, and results in RD18. Another hypothesis attributes changes in RD frequency to the seasonal change in behavior patterns . In summary, analysis of monthly and seasonal variations is insufficient to explain the association between meteorological factors and RD frequency, as these parameters may vary across regions.This study, performed in Kashiwa, Japan, showed that the highest RRD frequency was observed in summer and lowest in winter Fig. . However23, they have reported inconsistent results23. Some studies reported that RD frequency was associated with sunlight exposure, ambient temperature, and atmospheric pressure22, whereas two studies reported no correlation with ambient temperature, relative humidity, precipitation, or sunlight exposure23. In our study, we observed a negative correlation between atmospheric pressure and RD frequency, as previously reported18. The correlation between ambient temperature and RD frequency is also controversial: we observed no correlation, which was similar to some previous findings30; positive correlation was observed in one study18; and a negative correlation was observed in another15. Although there is some consensus on the mechanisms that may result in the seasonal variation of RD frequency, conflicting findings have made it difficult to conclusively determine how meteorological parameters influence RD frequency. Interestingly, our study showed that seven meteorological parameters (ADV) showed a significant negative correlation with RRD frequency, suggesting that meteorological stability plays an important role in RRD frequency. We speculated that meteorological stability would lead to an increase in physical activity, which in turn would result in vitreous instability. Instead of attributing changes in RRD frequency to individuals or a set of meteorological parameters, we hypothesize that the effect of overall meteorological stability may better explain our findings.To explain this association more precisely, we performed univariate analyses between 36 meteorological parameters and RRD frequency, identifying eight meteorological parameters that had significant negative coefficients. Among these, seven parameters could be categorized as ADVs. Although previous studies have also analyzed the association between meteorological parameters and RD frequencyWe developed three types of multivariate regression models using several meteorological parameters to predict RRD frequency. The third model (Model C) showed excellent AICc, BIC, CV-VE, and sustained VE using only six meteorological parameters, indicating that it could be used for predicting monthly RRD frequency with an accuracy of 84.82% (95% CI 75.18–93.72%). Our findings strongly suggest that a multivariate regression model is highly effective for predicting RRD frequency.31. There was no control for individual level confounders including smoking, comorbidity such as diabetes, socioeconomic status, and other similar factors. Some non-meteorological factors, such as some annual events which affect lifestyle or physical activity, may affect seasonal variations in the number of patients with RRD as previously suggested33. Further large-scale, multicenter, and prospective studies are necessary to establish a precise multivariate regression model that can predict monthly and daily RRD frequency.Our study had some limitations owing to its single-center study design. Our data had a selection bias because our hospital medicated patients with RRD with surgery and studied patients who underwent surgery. Also, it was difficult to fully analyze the effects of confounders because this was an ecological study that analyzed aggregated dataIn conclusion, this was the first study to investigate the association between meteorological parameters and RRD frequency in Japan. Our findings showed that specific meteorological parameters such as low atmospheric pressure and high meteorological stability have a significant correlation with high RRD frequency. In addition, we established the validity of our multivariate regression model  for the prediction of RRD frequency.


Background: Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease. The characteristic pathologies include extracellular senile plaques formed by β-amyloid protein deposition, neurofibrillary tangles formed by hyperphosphorylation of tau protein, and neuronal loss with glial cell hyperplasia. Circular RNAs (circRNAs) are rich in miRNA-binding sites , which serve as miRNA sponges or competitive endogenous RNAs (ceRNAs). Although several research groups have identified dysregulated circRNAs in the cerebral cortex of SAMP8 mice or APP/PS1 mice using deep RNA-seq analysis, we need to further explore circRNA expression patterns, targets, functions and the signaling pathways involved in the pathogenesis of AD and in particular the hippocampal circRNA expression profiles in AD.Methods: We used deep RNA sequencing to investigate circRNA-ceRNA network patterns in the hippocampus of APP/PS1 mice.Results: In our study, 70 dysregulated circRNAs, 39 dysregulated miRNAs and 121 dysregulated mRNAs were identified between the APP/PS1 group and the wild-type group at 8 months in the hippocampus of the mice. Through correlation analysis, we identified 11 dysregulated circRNAs, 7 dysregulated miRNAs and 8 dysregulated mRNAs forming 16 relationships in the circRNA-miRNA-mRNA regulatory network. Gene ontology (GO) analysis indicated that the dysregulated circRNAs were most enriched in biological metabolic processes. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the dysregulation of circRNAs was enriched in the cGMP-PKG signaling pathway, cAMP signaling pathway, Hippo signaling pathway, platelet activation, long-term potentiation and axon guidance. In addition, our findings preliminarily verified that the novel_circ_0003012/mmu-miR-298-3p/Smoc2 signaling axis may regulate the pathophysiology of AD by affecting the cGMP-PKG signaling pathway.Conclusions: These newly identified circRNAs in networks and signaling pathways reveal potential diagnostic or therapeutic targets for AD. Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease and is the most common type of senile dementia . The maiCircular RNA (circRNA) is a non-coding RNA with a unique covalent closed loop structure. CircRNAs are rich in miRNA-binding sites , which serve as miRNA sponges or competitive endogenous RNAs (ceRNAs) . CurrentIn previous studies, several research groups have identified dysregulated circRNAs in the cerebral cortex of SAMP8 mice or APP/PS1 mice using deep RNA-seq analysis . Other gDespite these findings, we need to further explore the expression patterns, targets, and functions of circRNAs and the signaling pathways involved in the pathogenesis of AD. Therefore, further research is of great importance. Here, we detected dysregulation of the circRNA-ceRNA profile in the hippocampus of APP/PS1 mice using deep RNA-seq analysis. We performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to predict the biological roles and potential signaling pathways of these differentially expressed circRNAs. Furthermore, we conducted circRNA-ceRNA network pattern analysis to further explore the potential roles of dysregulated circRNAs in AD pathogenesis. Taken together, our findings may promote a better understanding of the role of circRNAs in the neuropathogenesis of AD.Eight-month-old APP/PS1 mice and their age-matched wild-type mice were purchased from Model Animal Research Institute of Myhalic . The mice were housed two per cage under the standard conditions (12 h light/dark cycle at 25°C and 50 ± 10% relative humidity). We randomly selected nine animals from each group, three animals for RNA-seq, and six animals for Real-time qPCR. Animals administered general anesthesia and then collected hippocampal tissue. Animal care and experimental procedures were implemented according to the document “Guidance Suggestions for Caring for Laboratory Animals” produced by the Ministry of Science and Technology of China in 2006.Total RNA was extracted from each hippocampal tissue sample by RNAprep Pure Tissue Kit  in accordance with the manufacturer’s instructions.® spectrophotometer to check the RNA purity  and using Qubit® RNA Assay Kit in Qubit® 2.0 Flurometer to measure the RNA concentration . Finally, using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system to assess the RNA integrity .Using 1% agarose gels to monitor RNA degradation and contamination. Then, using the NanoPhotometerDetails of the mRNA-seq, miRNA-seq, and circRNA-seq methods are described in TM RT reagent Kit with gDNA Eraser  according to the manufacturer’s instruction.To validate the RNA-Seq data, we randomly selected 3 of circRNA, miRNA and mRNA for qRT-PCR analysis, respectively. Total RNA was extracted from each hippocampal tissue sample, and then reverse-transcribed into cDNA using PrimeScript® Premix Ex TaqTM II (Tli RNase H Plus) Kit with a Bio-Rad CFX Manager 3.1 real-time PCR system . The relative circRNA and mRNA expression levels were calculated using the 2–ΔΔCt method and were normalized to GAPDH as an endogenous reference transcript. miRNA expression levels were normalized to that of U6. The specific primers for each gene are listed in Real-time quantitative PCR (RT-qPCR) was performed using the SYBR1. We used clusterProfiler R package to test the statistical enrichment of aberrantly expressed circRNAs in KEGG pathways. GO and KEGG terms with corrected P-value < 0.05 were considered significantly enrichment of aberrantly expressed circRNAs.Gene Ontology (GO) enrichment analysis of differentially expressed genes was conducted by clusterProfiler, an R package for functional classification and enrichment of gene clusters using hypergeometric distribution. KEGG is a database resource for understanding high-level functions and utilities of the biological system2 and miRanda3. The circRNA-miRNA-mRNA network covered two cases: upregulated circRNA-downregulated miRNA-upregulated mRNA, and downregulated circRNA-upregulated miRNA-upregulated mRNA. Then, we constructed circRNA-miRNA-mRNA network using the Cytoscape software V2.7.0 .We have selected the differentially expressed circRNA, miRNA and mRNA that have been identified. CircRNA-miRNA interactions and miRNA-mRNA interactions were predicted with Arraystar’s home-made miRNA target prediction software based on TargetScanp < 0.05 was statistically significant.Statistical analyses were performed using SPSS v16.0 software . All data were expressed as the mean ± SEM. 4 and the unmapped reads were subsequently selected  mice, and 258,658,168 for APP/PS1 mice. Removed poly(N)-containing, low-quality, and adaptor-containing reads from the raw data, then remained 506,341,272 clean reads including 251,602,810 for wild-type and 254,738,462 for APP/PS1 mice. The high-quality clean data were mapped to the mouse reference sequence by Hisat2selected . circRNAselected . These cA total of 90,306,346 raw reads were generated, 42,973,163 for WT mice, and 47,333,183 for APP/PS1 mice. After removal of low-quality and adaptor sequences, 41,501,993 clean reads for WT group and 46,256,666 clean reads for APP/PS1 group were remained. The reads we selected are mostly based on the length of 21–22 nt in both groups. These reads were annotated and classified based on previous studies . FinallyA total of 267,484,154 raw reads were generated: 135,704,866 for APP/PS1 mice, and 131,779,288 for wild-type mice. After discarding the reads with adapters, poly-N > 10%, and discarding the low-quality reads. 211,535,266 UMI reads were obtained: 107,820,630 for APP/PS1 mice, and 103,714,636 for wild-type mice. The clean reads were mapped to the mouse reference genome, and the Dedup2MappedUMI rates were approximately 80.50% for APP/PS1 mice and 85.08% for wild-type mice. The cufflink results indicated that 57,077 protein-coding transcripts were identified. These mRNAs were used for the subsequent analysis.p < 0.05), of which 44 circRNAs were upregulated and 26 were downregulated (We identified 70 significantly aberrantly expressed circRNAs between APP/PS1 mice and wild-type (WT) mice at 8 months in the hippocampus (egulated . We perfegulated .p < 0.05), of which 16 miRNAs were upregulated and 23 were downregulated , with 34 upregulated mRNAs and 87 downregulated mRNAs  5 (4/44), chr. 16 (4/44), and chr. 17 (4/44), while the top two chromosomes for the downregulated circRNAs were chr. 1 (3/26) and chr. 3 (3/26). As for localization of the dysregulated circRNAs, there were 40 exonic and 4 intronic in the upregulated circRNAs and 25 exonic and 1 intronic in the downregulated circRNAs .We used RT-qPCR to confirm the differentially expressed RNAs in our RNA-seq experiments. We randomly selected three circRNAs, three miRNAs and three mRNAs to perform RT-qPCR. As shown in Cst7) were significantly different between the hippocampal tissues of 8-month-old APP/PS1 mice and 2-month-old APP/PS1 mice (P < 0.05)  . This reGene Ontology (GO) analyses were performed on the circRNAs, and the top highly significantly enriched GO terms of the dysregulated circRNAs on biological process (BP) and molecular function (MF) are shown in organophosphate metabolic process (GO: 0019637), nucleotide metabolic process (GO: 0009117) and nucleoside phosphate metabolic process (GO: 0006753). Several metabolic pathway-related terms were also observed, such as pyrimidine nucleobase metabolic process (GO: 0006206), ribonucleotide metabolic process (GO: 0009259) and ribose phosphate metabolic process (GO: 0019693). In summary, the pathological progression of AD may be associated with several metabolic pathways regulated by circRNAs.In addition, we also performed GO analysis of miRNAs and mRNAs. Through GO analysis of miRNAs, we found that the 20 top terms enriched in BP, cellular component (CC) and MF were almost all associated with cellular metabolic process, intracellular organelle/part and binding functions : cellulaKyoto Encyclopedia of Genes and Genomes pathway analysis was performed to determine the signaling pathways related to the dysregulated circRNAs. By using the Q-value scale from 0 to 1, the top 20 significantly enriched pathways were identified, as shown in Kyoto Encyclopedia of Genes and Genomes pathways were associated with dysregulated miRNAs involved in the MAPK signaling pathway, Ras signaling pathway, endocytosis, focal adhesion, axon guidance, neurotrophin signaling pathway and glycerophospholipid metabolism . KEGG paCircRNAs have MREs, which can be used as miRNA sponges to competitively bind miRNAs, thereby inhibiting miRNA targets to mRNA and indirectly regulating mRNA expression. Based on ceRNA theory, to search for circRNA-miRNA-gene pairs with the same MREs, circRNA-miRNA-gene pairs were constructed with the circRNA as a decoy, the miRNA as the core, and the mRNA as the target to construct a ceRNA regulatory network. The circRNA-ceRNA network pattern can show the regulation of the circRNA on the related mRNA-encoding genes.Based on the RNA-seq data, we selected 11 dysregulated circRNAs, 7 dysregulated miRNAs and 8 dysregulated mRNAs, and there were 16 relationships contained in the constructed circRNA-miRNA-mRNA regulatory network . The ceRThrough KEGG analysis, we obtained key regulatory signaling pathways, including the cGMP-PKG signaling pathway, cAMP signaling pathway, and Hippo signaling pathway. These pathways have been reported to participate in key regulatory roles in neurodegenerative diseases.We further explored the regulatory effects of the differential expression of circRNAs on the cGMP-PKG signaling pathway, cAMP signaling pathway, and Hippo signaling pathway. We searched for the differentially expressed circRNAs enriched in the 3 signaling pathways and obtained five circRNAs that might be involved in the cGMP-PKG signaling pathway: novel_circ_0002311, novel_circ_0009273, novel_circ_0003012, novel_circ_0003089, and novel_circ_0001331. Four circRNAs might be involved in the cAMP signaling pathway: novel_circ_0006299, novel_circ_0003012, novel_circ_0003089, and novel_circ_0001331. Two circRNAs might be involved in the Hippo signaling pathway: novel_circ_0008567 and mmu_circ_0000585.We predicted differentially expressed miRNAs that interact with those circRNAs and found that novel_circ_0009273, novel_circ_0003012, novel_circ_0006299, novel_circ_0008567, and mmu_circ_0000585 could target mmu-miR-3074-1-3p, mmu-miR-298-3p, mmu-miR-296-3p, mmu-miR-298-5p, mmu-miR-3074-1-3p, and mmu-miR-669e-5p, respectively.Through the predictive analysis of miRNA-mRNA interactions, we identified the downstream target mRNAs that might be regulated and constructed a circRNA-ceRNA network related to the three signaling pathways . Based op < 0.05).Furthermore, we also verified whether the circRNA-ceRNA network affects the cGMP-PKG signaling pathway. As shown in Preliminary verification of the regulatory role of the novel_circ_0003012/mmu-miR-298-3p/Smoc2 signaling axis in the pathology of AD showed that it involved the downregulation of PKG.Cst7 (ENSMUSG00000068129). Cst7 (cystatin F) encodes an endosomal/lysosomal cathepsin inhibitor that regulates cathepsin activity in the lysosomal pathway , 7 dysregulated miRNAs (4 upregulated miRNAs and 3 downregulated) and 8 dysregulated mRNAs (3 upregulated mRNAs and 5 downregulated), forming 16 relationships in the circRNA-miRNA-mRNA regulatory network. Our results showed that the aberrantly expressed circRNAs had miRNA-binding sites and were thus predicted to play a regulatory role via the ceRNA mechanism . These c pathway . The exp pathway .The GO analysis was performed to further annotate the biological functions related to the aberrantly expressed circRNAs. The top GO terms of the differentially expressed circRNAs were most enriched in biological metabolic processes, such as phosphorus metabolic process, organophosphate metabolic process, nucleotide metabolic process, nucleoside phosphate metabolic process, pyrimidine nucleobase metabolic process, ribonucleotide metabolic process and ribose phosphate metabolic process. This result indicated that the pathological progression of AD may be associated with several metabolic pathways regulated by circRNAs. In addition, we also performed GO analysis of miRNAs and mRNAs. The top terms of miRNAs were almost all associated with cellular metabolic process, intracellular organelle/part and binding functions. The dysregulated mRNAs were mostly enriched in cellular/organism development processes or cell differentiation.As the main components of nucleic acids, nucleobases, nucleosides, nucleotides and related phosphorylated metabolites have many important roles as intermediates in biosynthetic pathways in biological systems . There ide novo pyrimidine biosynthesis. A decrease in the de novo synthesis of pyrimidine nucleotides leads to dysfunction of the OXPHOS system and to the pathogenesis of late-onset AD  system . The OXPonset AD . Disordeonset AD . Severalonset AD . All theKyoto Encyclopedia of Genes and Genomes analysis showed that the dysregulation of circRNAs was enriched in many signaling pathways, which are closely related to the pathogenesis of AD, including the cGMP-PKG signaling pathway, cAMP signaling pathway, Hippo signaling pathway, platelet activation, LTP and axon guidance. KEGG pathway analysis of dysregulated miRNAs and mRNAs also identified enrichment in focal adhesion, axon guidance, platelet activation and the Hippo signaling pathway. In particular, the signaling pathways of miRNA and mRNA enrichment, such as platelet activation, axon guidance and the Hippo signaling pathway, were consistent with the KEGG analysis of circRNAs.Other studies have also reported that several dysregulated circRNAs in the cerebral cortex of AD mice are enriched in the PI3K-Akt signaling pathway, tight junctions, Hippo signaling pathway, LTP and axon guidance . These r1–42  and the cGMP controller phosphodiesterase are critical participants in the neuroinflammatory process, which may lead to neurological dysfunction, cell death and further neurodegeneration . The inc of APPS . Our resFrom the results of the circRNA-ceRNA network constructed on the basis of the differentially expressed circRNAs, miRNAs and mRNAs obtained from the sequencing analysis results and the series of circRNAs predicted by KEGG analysis that are closely related to the cGPM-PKG signaling pathway, we found that the novel_circ_0003012/mmu-miR-298-3p/Smoc2 signaling axis may be closely related to the pathological mechanism of AD.Through preliminary verification, we found that the differential expression of novel_circ_0003012 and mmu-miR-298-3p may regulate the pathological mechanism of AD by affecting the cGPM-PKG signaling pathway.In summary, we elucidated the circRNA-ceRNA network patterns in the hippocampus of APP/PS1 and WT mice by using deep RNA-seq analysis. Our findings further expand the current knowledge regarding the biology of circRNA-ceRNA, their involved signaling pathways, such as the dysregulated circRNAs in nucleotide metabolism, cGMP-PKG signaling pathway, cAMP signaling pathway, platelet activation and Hippo signaling pathway, and their regulatory roles in AD pathogenesis. In addition, our findings preliminarily verified that the novel_circ_0003012/mmu-miR-298-3p/Smoc2 signaling axis may regulate the pathophysiology of AD by affecting the cGMP-PKG signaling pathway. These newly identified circRNAs in networks and signaling pathways reveal potential diagnostic or therapeutic targets for AD.https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA712946.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: The animal study was reviewed and approved by Medical Ethics Committee of Qingdao University.YZ conceived and wrote the manuscript. YZ and LQ reviewed and edited the manuscript. YLy, YLg, WY, and YZf participatedin literature search, data collection, and figures design. All authors read and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Angelicae Pubescentis Radix in rheumatoid arthritis treatment is complex; the pathways and protein targets involved remain unclear. This study predicted the targets and signaling pathways of Angelicae Pubescentis Radix for rheumatoid arthritis treatment using network pharmacology and molecular docking technology and clarified its mechanism of action using in vitro cellular experiments.The mechanism of action of Angelicae Pubescentis Radix active components and related targets were retrieved from the traditional Chinese medicine systems pharmacology database. All human proteins were mined from the global protein database, and the network of active components and targets of Angelicae Pubescentis Radix was drawn using Cytoscape 3.7.1. GeneCard, Online Mendelian Inheritance in Man, and DrugBank databases were used to mine rheumatoid arthritis-related genes. Metascape was used for Gene Ontology function analysis and Kyoto Encyclopedia of Genes and Genomes enrichment pathways. β-sitosterol’s molecular docking was determined using AutoDock Tools; pathway verification was performed in the Kyoto Encyclopedia of Genes and Genomes database, and the verified genes were input into the Human Protein Atlas database to observe the expression levels in various human body tissues.Angelicae Pubescentis Radix from the traditional Chinese medicine systems pharmacology database, and 60 targets related to major active ingredients were obtained. Forty-two core pathogenic rheumatoid arthritis-related genes were screened from GeneCard and other related databases. The enrichment of the Kyoto Encyclopedia of Genes and Genomes pathway included the vascular endothelial growth factor signaling pathway that proved to be the decisive pathway for rheumatoid arthritis treatment by a high degree value. In vitro experiments confirmed that Angelicae Pubescentis Radix mainly regulated cell proliferation and survival through the vascular endothelial growth factor signaling pathway and showed significant therapeutic effects on rheumatoid arthritis. The prostaglandin endoperoxide synthase 2 gene was associated with rheumatoid arthritis via pathway verification and monitoring of human gene expression levels.Eight main active components were screened out of Angelicae Pubescentis Radix was explored using network pharmacology and molecular docking technology, providing new thinking and research directions for future rheumatoid arthritis treatment using Angelicae Pubescentis Radix.The mechanism of the multi-component, multi-target, and multi-channel treatment of rheumatoid arthritis via The online version contains supplementary material available at 10.1186/s12906-022-03769-w. Rheumatoid arthritis (RA) is a chronic autoimmune disease with characteristics of symmetry, progression, and invasion . It has Angelicae Pubescentis Radix, the dried roots of Angelica biserrata C.Q.Yuan & R.H.Shan (a synonym for Angelica pubescens f. biserrata R.H. Shan & C.Q. Yuan in Chinese Pharmacopoeia), is currently used as a medicine. It has recently been verified to have anti-inflammatory, analgesic, sedative, and anti-tumor effects, as well as the short-term effects of lowering blood pressure and inhibiting platelet aggregation [Angelicae Pubescentis Radix is currently used to treat soreness of the waist and knees, rheumatism, and arthralgia. It is commonly used for the treatment of RA. However, its therapeutic mechanism is unclear, and further research regarding its mechanism is needed. Therefore, an exploration of the active components of Angelicae Pubescentis Radix is necessary, and its mechanism for the treatment of diseases such as RA should be determined to provide a basis for future pharmacological research.regation . AngelicAngelicae Pubescentis Radix for the treatment of RA can be explored at the molecular level through network pharmacology and molecular docking technology. The network of the active components, targets, and dredging collaterals of Angelicae Pubescentis Radix can be constructed and clarified via multiple aspects, revealing its pharmacodynamic components and mechanism of action for the treatment of RA [The mechanism of action of nt of RA . This woAngelicae Pubescentis Radix for the treatment of RA using network pharmacology and molecular docking technology. In addition, we aimed to clarify and verify the mechanism of action using in vitro cellular experiments. Fig. This study aimed to predict the targets and signaling pathways of Angelicae Pubescentis Radix were retrieved from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) [The medicinal components of  (TCMSP) .Traditional Chinese medicines (TCMs) need to be distributed rapidly in the process of absorption, distribution, metabolism, and excretion (ADME). In ADME, oral bioavailability (OB) is one of the most representative pharmacokinetic parameters; thus, substances with OB ≥30% have higher druggability.Druglikeness (DL) is used as a qualitative concept to estimate the drug properties of molecules in drug design. The DL index can be used to quickly screen active substances, and substances with DL ≥0.18 are considered to have druggability.Angelicae Pubescentis Radix with OB ≥30% and DL ≥0.18 were chosen as the active ingredients in this experiment.Therefore, the compounds of http://www.Uniprot.org). Active component targets retrieved from the TCMSP database were compared with the Uniprot database to obtain standard gene names.All human protein and gene data were downloaded from the global protein resource database , Online Mendelian Inheritance in Man , and DrugBank (http://www.go.drugbank.com) databases were searched using the keyword “rheumatoid arthritis” [The human genes  to construct a target network using the “organization” option. The minimum required interaction score was set to have medium reliability of 0.400. No maximum number of associates was set. The association importance and interaction of each node were determined using the difference in the degree values.The target genes of the components of Homo sapiens to clarify the roles of the target proteins in the gene functions and signaling pathways [P-value of < 0.05 was set as the threshold value, and statistical significance was set at a P-value < 0.05.The Metascape database and were used to conduct a functional enrichment analysis of the Gene Ontology (GO) and a pathway enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway with the background set as pathways –11. Funchttp://cytoscape.org [To further visualize the molecular mechanisms of the active ingredients against RA, the obtained data were organized into network and type files that were imported into Cytoscape version 3.7.1 , an open-source software available at cape.org . The sofMolecular docking includes three steps: (a) preparation of ligands, (b) preparation of macromolecules (targets) and determination of their active sites, and (c) ligand-target docking.Here, a two-dimensional structure of β-sitosterol was obtained using PubChem software  and stored in the SDF format that was processed using ChemBio3D  to obtain a three-dimensional structure with minimum energy.The target’s crystal structure was obtained from the Protein Data Bank, and the water molecules and hydrogenation were removed using PyMOL software .Angelicae Pubescentis Radix, and the 10 genes with the highest degree values in the protein-protein interaction (PPI) network. Molecular docking was assessed using Autodock Vina software (Scripps Research Institute) to evaluate the binding of β-sitosterol and the target based on the binding energy standards, and visual processing was performed using PyMOL software.Autodock Tools software  was used to convert the three-dimensional structure of β-sitosterol and crystal structure of the target into the pdbqt format. Molecular docking was conducted with β-sitosterol, a key active component in MH7A rheumatoid arthritis fibroblast cells (lot number 21112414) were purchased from Beina Bio .Dulbecco’s modified eagle medium ; β-sitosterol , fetal bovine serum , phosphate buffer saline , pancreatin , DMSO , MTT , a BCA kit , an ECL high-sensitivity chemiluminescent solution kit , β-actin , VEGFA , PTGS2 , VEGFR2 , and horseradish peroxidase-labeled goat anti-rabbit IgG secondary antibody  were used in this study.2 incubator , clean bench , centrifuge , microplate reader , electrophoresis instrument , decoloring shaker , and chemiluminescence analyzer  were used in this study.A CO2. The cells were divided into blank, control, and medication groups. When the cell density reached 80%, β-sitosterol was added to the medication group at gradient concentrations . After 24 h, 5 μg/mL MTT solution was added, and the cells were cultured for 4 h, after which the supernatant in the wells was discarded, and 150 μL DMSO was added to each well. The solution was shaken on a shaking table in the dark for 10 min until the crystals were completely dissolved. The optical densities (ODs) of the well plates were measured using a microplate reader at 570 nm and compared with the OD of the control group to determine the relative cell activity.The proliferation of MH7A cells was detected using the MTT cell proliferation assay. Cells in the logarithmic phase were inoculated on culture plates and incubated for 24 h and 48 h at 37 °C with 5% CO5/L, and 100 μL of binding buffer, 5 μL of annexin V-phycoerythrin, and 5 μL of 7-amino-actin D were added.The effects of β-sitosterol on the cell cycle and apoptosis were detected using flow cytometry. MH7A cells in the logarithmic phase were inoculated into 96-well plates and were incubated with gradient concentrations of β-sitosterol for 24 h. Then, the cells were digested with trypsin, centrifuged at 1500 r/min for 5 min, and washed with PBS. The supernatant was discarded after centrifugation, and the cells were fixed with 2-mL 75% ethanol at 4 °C for 12 h. The cells were centrifuged, the supernatant was removed before two washes with PBS were conducted, and 500 μL of propidium iodide and ribonuclease mixture was added. For the apoptosis analysis, the cell concentration was adjusted to 1 × 10Cells were lysed with radioimmunoprecipitation assay lysis buffer on ice for 30 min and centrifuged at 1200 r/min at 4 °C. The supernatant was used for protein quantitative detection via the BCA method. The protein samples were denatured and stored at − 20 °C. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis was conducted, followed by membrane transfer via blocking with TBST containing 5% defatted milk powder for 2 h. The membrane was incubated with antibodies against VEGFA, VEGFR2, or PTGS2 for 12 h at 4 °C and then washed with TBST . The membranes were then incubated with secondary antibodies (horseradish peroxidase-labeled) for 2 h at room temperature and were washed again with TBST . The membrane was developed using the ECL chemiluminescent color method and ImageJ software .P < 0.05 was considered to indicate a statistically significant difference.Experimental data are shown as means±standard deviations. SPSS 22.0  software was used for statistical analysis. One-way analysis of variance was used for multi-group comparison, and the t-test was used for inter-group comparison. Angelicae Pubescentis Radix were identified. Eight active components met the screening criteria, which mainly comprised coumarin compounds , sterol compound (β-sitosterol), polysaccharide compounds (Angelicone nodakenin), and so on . The core genes were identified as VEGFA, JUN, and NOS3  enrichment analysis. A total of 761 biological processes were enriched, and 43 cell components and 50 molecular functions were obtained. The biological processes included the vascular processes in the circulatory system, regulation of muscle, muscle system processes, response to ammonium ion, and calcium ion transport. The cellular components included a plasma membrane raft, membrane raft, membrane microdomain, and membrane region. The molecular functions of an integral component of the postsynaptic membrane included G protein-coupled amine receptor activity, neurotransmitter receptor activity, ammonium ion binding, G protein-coupled neurotransmitter receptor activity, and neurotransmitter binding  signaling in diabetic complications, vascular endothelial growth factor signaling, apoptosis of multiple species, Parkinson’s disease, platinum drug resistance, and pancreatic cancer , NOS3 (PDB ID: 1M9J), PTGS2 (PDB ID: 5F19), and SLC6A3 (PDB ID: 4XPF) were visualized. β-sitosterol was connected with the amino acid residue PHE-473 of the NOS3 gene via hydrogen bonds, while β-sitosterol and GLU-524 were connected via hydrogen bonds at the amino acid residue of PTGS2 Table .Table 3BPTGS2 was identified as an inflammatory factor in the VEGF pathway that promotes the production of PGI2. PTGS2 was identified as cyclooxygenase-2 (COX-2) in the KEGG database and network pharmacology, a key enzyme that promotes the synthesis of prostaglandins from arachidonic acid. Prostaglandins are involved in the inflammatory process Fig. .Fig. 9CeThe expression levels of NOS3 and PTGS2 in human tissues were obtained from the Human Protein Atlas database. PTGS2 was present and expressed in soft tissues, indicating that the expression of PTGS2 is related to the development of RA Fig. .Fig. 10EP < 0.01)     and a marker of the proliferation and invasion of RA cells –19. AP-1Angelicae Pubescentis Radix may exert therapeutic effects on RA mainly by regulating cell proliferation and cell survival of RA through the VEGF signaling pathway. The VEGF signaling pathway works with several other pathways to regulate the angiogenesis process and is the most important pathway to promote neoangiogenesis and generate pannus. Therefore, the VEGF signaling pathway is a landmark pathway to clarify the pathogenesis of RA and monitor the development of RA.As predicted by network pharmacology, To further verify this hypothesis, we studied the therapeutic effect of β-sitosterol on RA cells in vitro. β-sitosterol significantly inhibited the activity and proliferation of RA cells, reduced the distribution of the G0/G1 phase of cells, and promoted the transformation of cells to the S phase. The results of Western bolt showed that β-sitosterol inhibited the proliferation and invasion of RA, significantly reduced the expression of PTGS2, VEGFA, and VEGFR2 proteins in a dose-dependent manner, and inhibited the VEGF signaling pathway. The VEGF signaling pathway has been confirmed to mediate endothelial cell proliferation, migration, and anti-apoptosis and improve vascular permeability. The high expression of VEGF in joint fluid and in the serum of patients with RA indicates that it is related to the progression of RA . Taken tAngelicae Pubescentis Radix, it is not the only active component. Therefore, further verification of other ingredients is required.This study was not without limitations. As the public database is updated in real-time, the mechanism of β-sitosterol in the treatment of RA is partially unclear. In this study, human RA cells were used. Therefore, multi-dimensional and multi-faceted studies are required to fully explore the mechanism of β-sitosterol in the treatment of RA. Although β-sitosterol is the main active component of Angelicae Pubescentis Radix used to treat RA. The roles of the core targets and signaling pathways for regulating immunity, providing anti-inflammatory effects, and inhibiting inflammatory factors have been clarified. The identification of the key targets of Angelicae Pubescentis Radix during the treatment of RA allows for further elucidation of its pharmacological effects, which will improve the treatment methods for RA.This study determined the complex relationship between the components, targets, and pathways of Additional file 1: Figure S1. Original picture of protein expression level.


Furthermore, molecular docking was performed using the Autodock against majorly targeted proteins  with the selected 52 tripeptides. The interaction model between tripeptides and targets was mainly hydrogen-bonding and hydrophobic interactions, and most of the binding energy of the tripeptide target was less than −7.13 kcal/mol. This work can provide valuable insight for exploring food-derived tripeptide mechanisms and therapeutic indications.Food-derived tripeptides can relieve colitis symptoms; however, their alleviation mode has not been systematically evaluated as an alternative nutritional compound. This study aimed to reveal the potential mechanism of 8000 food-derived tripeptides against acute colitis using a computer-aided screening strategy. Forty-one potential hub targets related to colitis with a Fit score > 4.0 were screened to construct the protein-protein and protein-tripeptide network based on the PharmMapper database and STRING software (Ver. 11.5). In addition, 30 significant KEGG signaling pathways with  Inflammatory bowel disease (IBD) has been recognized as a chronic, incurable, and idiopathic disease spreading worldwide. Therefore, alleviating IBD has become an emerging challenge for public health ,2,3. AcuSmall-molecule active peptides extracted from food-derived proteins have nutritional supplementation  and physNetwork pharmacology is an interactive network based on the concept of “disease-gene-target-compounds”, which treats the intervention and effect of active compounds on the disease network from a systematic and comprehensive perspective to reveal the complex mechanisms of active compounds ,18,19. TBased on the pharmacology analysis results, 41 predicted gene targets were screened to construct the set hub targets . The PPIA tripeptide-target network performed the complex interaction between tripeptides and the screened hub targets. Based on the PharmMapper and GeneCards analysis, tripeptides (related to the most hub targets) were summarized and ranked in the present study. Fifty-two tripeptides were chosen for further tripeptide-target PPI analysis. In GO functional enrichment was performed based on both FunRich (Ver. 3.1.3) and DAVID software (Ver. 6.8) to investigate the function of the selected hub target genes. p-values and are exhibited as bar charts in p-value = 3.81 × 10−10), intracellular signal transduction , and the protein phosphorylation term . The top three CC terms were the cytosol , nucleus , and plasma membrane , respectively. Meanwhile, the top three enrichment MF categories were protein binding , ATP binding , and protein homodimerization activity .Furthermore, the DAVID database’s GO enrichment of significant terms for CC, BP, and MF were ranked by p-value < 0.001) were further investigated and are shown in a bubble map  revealed the selected 41 hub targets’ organ expression sites . The aboTopological analysis results of the thirty hub targets showed that targets of AKT1, EGFR, and MMP9 had a higher “degree value” and “closeness centrality”, as shown in Reference ligands obtained from AKT1, EGFR, and MMP9 crystal structures, were first considered to optimize the rationality docking conditions. The above three reference ligand structures had highly overlapped before and after docking with RMSD (root-mean-square deviation) values of 0.83 Å, 1.46 Å, and 3.36 Å, respectively . MeanwhiAfter optimizing the docking conditions, the selected 52 tripeptides were all docked with the above three targets’ protein crystal structures, respectively. Results revealed that these 52 tripeptides showed lower binding energy with the targets of AKT1, EGFR, and MMP9  to predict the potential colitis-related targets [http://www.uniprot.org/; accessed on 16 November 2021) to exclude the same targets and non-Homo sapiens targets. Meanwhile, targets related to colitis obtained from the GeneCards Human database  were used to improve the objective tripeptide hub targets set.Firstly, the structures of 8000 food-derived tripeptides were constructed. Then, the UCSF Chimera software (Ver. 1.15) was used to obtain the tripeptide energy minimization structures . Afterwa targets . Based ohttp://string-db.org/; accessed on 25 November 2021) to assess the potential interactions between the 41 screened hub targets [https://cytoscape.org/; accessed on 2 December 2021) [The PPI network was constructed using the STRING database ( targets . The inter 2021) . Furtherer 2021) ,38.http://david.abcc.ncifcrf.gov/home.jsp; accessed on 20 December 2021) has been reported to help integrate functional genomic annotations with intuitive graphical summaries [p-value < 0.05) and KEGG pathways  were considered for further evaluation. Finally, the data were visually displayed using the free bioinformatics database .The DAVID database  to research the selected hub target’s main organ site expression based on the “Human proteome” database. The result was displayed in the form of a heatmap. The positively correlated high-expressed targets in the organs are shown in red, while the low-expressed targets are marked in blue. The higher the expression level of the target, the darker the color.http://www.rcsb.org/pdb; accessed on 3 January 2022) [Subsequently, AutoDock 4.2 was used to evaluate the interaction between tripeptides and the above three hub targets . Based ory 2022)  for furtry 2022) ,48.To verify the rationality-optimized docking conditions, the reference ligands of AKT1, EGFR, and MMP9 crystal structures were first considered. A Lamarckian genetic algorithm as the search engine searched 200 runs. During docking, the grid spacing was set to 0.375 Å . The finBased on the computer-aided screening strategy, this study has systematically investigated the potential effects of 8000 tripeptides to alleviate acute colitis, including the possible pleiotropic pathways. Tripeptides play a role in relieving colitis by regulating signaling pathways, such as inflammation, immunomodulation, and cell proliferation and differentiation, especially in the Ras- and PI3K-Akt signaling pathways. This work provides a computer-aided method for screening potential functional targets of active ingredients, which can provide a reference for the functional mining of food-derived peptides.


Radix Salvia miltiorrhiza.  The aim of the study is to explore the molecular mechanism of activating blood circulation and dispersing stasis herbs in the treatment of pre-eclampsia with Chuanxiong Rhizoma-Radix Salvia miltiorrhiza were retrieved from the TCMSP database, and a PPI network was constructed for common genes. Subsequently, a graph of the “active component-target-action pathway” was plotted by Cytoscape 3.7.2 and a KEGG pathway enrichment was performed using the R language cluster profiler package. Molecular docking was conducted between the top five PPI targets of Chuanxiong Rhizoma-Radix Salvia miltiorrhiza.  The chemical composition and targets of Chuanxiong Rhizoma-Radix Salvia miltiorrhiza, and its most evident effects were exerted on G-protein-coupled amine receptors and the neuroactive ligand-receptor interaction signaling pathway. Molecular docking indicated that the target protein had a good binding ability with the drugs.  According to network pharmacology, there were 32 target genes, 60 active components, and 59 pathways in Chuanxiong Rhizoma-Radix Salvia miltiorrhiza have therapeutic effects in pre-eclampsia, as confirmed by the results of molecular biology analysis. Thus, the Chuanxiong Rhizoma-Radix Salvia miltiorrhiza regimen provides a basis for the treatment of pre-eclampsia using traditional Chinese medicine. Chuanxiong Rhizoma- Pre-eclampsia (PE) is a disorder of pregnancy characterized by the new onset hypertension with multiple system involvement and damage after 20 weeks of pregnancy. PE is responsible for the deaths of more than 500, 000 neonates, fetuses, and 70, 000 maternal deaths worldwide, with a global incidence rate of 2%∼8% . Severe From the perspective of traditional Chinese medicine, PE belongs to the category of “gestational vertigo”. Most PE patients are mixed with blood stasis syndrome. Therefore, the drugs used for syndrome differentiation should be properly administered to promote a healthy blood circulation and treat the blood stasis . CR-RSM https://tcmspw.com/tcmsp.php), OB ≥ 30% and DL ≥ 0.18 were used as thresholds to detect the drug components and target genes of CR-RSM, respectively [In the TCMSP database | > 1 were considered as targets with statistically significant difference in the PE expression.By searching the targets of pre-eclampsia in GEO data sets , the selThe predicted genes of CR-RSM were mapped to PE pathologic genes to obtain the target genes of CR-RSM for PE treatment. The target gene set of CR-RSM was analyzed to determine the common target genes and input into the Cytoscape 3.7.2 software plugin BioGenet . ThereafThe topology important nodes in the network were filtered out using degree centrality (DC), betweenness centrality (BC), closeness centrality (CC), eigenvector centrality (EC), the local average connectivity-based method (LAC), and network centrality (NC) with the Cytoscape plugin CytoNCA.R language to classify and enrich proteins; while the Kyoto Encyclopedia of Genes and Genomes (http://www.genmoe.jp/keg) database was used to analyze the related signal pathways. We subsequently explored the gene pathway network of these genes with significant regulatory pathways and built a gene pathway network to determine the mechanism of action of CR-RSM in the treatment of PE.For further evaluation of the target's biological functions, GO analysis with the biological process, cell composition and molecular function annotation of candidate targets were analyzed using the clusterProfiler package  in R lanhttps//:www.rcsb.org). The combination of NTRK1, APP, TP53, CUL3, and ESR1 as well as CR-RSM were transformed into a PDBQT format by AutoDock Tools 1.5.6 [Molecular docking technology is based on the simulation of ligand receptor interactions  to predict the binding mode and affinity between proteins and proteins or peptides, so as to perform the virtual screening of drug inactive and active components. ChemBio3D Ultra 17.0 was used to illustrate the structures of compounds in CR-RSM, which were then transformed into three-dimensional structures by ChemBio3D Ultra 17.0 and optimized using the MMFF94 force field. The target proteins NTRK1, APP, TP53, CUL3, and ESR1 were selected from the top 5° in the PPI network, and their three-dimensional structures were downloaded from the RCSB protein data bank  were screened out . Whilst,The compound network of CR-RSM were constructed using the selected compounds and their targets . The comIn order to reveal the mechanism of action of CR-RSM in the treatment of PE, the target gene sets of CR-RSM and PE were analyzed. The common target gene was the PPI network composed of 3521 nodes and 50004 edges . The PPIR language, and the GO pathway was further explored in terms of the biological process, cell composition, and molecular function. A total of 766 go items were significantly enriched (FDR <0.05), with 700 enriched in the biological processes, 25 were enriched in the cell components, and 42 were enriched in molecular function. The top 20 terms ranked by p value are displayed in G protein coupled amine receptor activity.The GO and KEGG pathways of 32 candidate targets were analyzed using the clusterProfiler package of pvalues and the number of target genes involved. The top 20 pathways are delineated in KEGG pathway analysis confirmed that CR-RSM plays a crucial role in the treatment of PE. A total of 59 enrichment pathways (FDR <0.05) were identified, which were ranked according to their Gene pathway networks were constructed based on enriched pathways and genes regulating these pathways ,the detaThe interaction strength between small molecules and proteins can be expressed by the docking fraction; the higher the score, the higher the interaction intensity. Generally speaking, a score >4.25 indicates a certain binding activity, while a score >5.0 suggests a good binding activity and a score >7.0 indicates a strong binding activity . ThroughWith the in-depth study on the theoretical hypotheses of traditional Chinese medicine, it is now believed that PE is closely related to “blood stasis”. The Yin blood accumulates to nourish the fetus during pregnancy, resulting in Yin blood deficiency and blood flow disturbances, or the presence of the fetus in the abdomen hinders the Qi mechanism, leading to impaired blood flow, which results in blood stasis . Modern The compound network consisted of 60 compounds and 32 targets. The results revealed that the active ingredients in CR-RSM had effects on many several therapeutic targets. Cryptotanshinone, myricetin, and luteolin acted on 14, 10, and 5 targets, respectively. Therefore, these compounds are most likely the important multidirectional active ingredients of CR-RSM. Even though the number of targets predicted by each compound is different, there are many overlapping targets, that is, multiple compounds in CR-RSM may have the same target, thus acting in a synergizing manner. Cryptotanshinone is a fat soluble compound in tanshinone, which has antibacterial, anti-inflammatory, and antioxidant effects. It can also significantly promote vascular regeneration, reduce platelet aggregation and adhesion, and improve erythrocyte denaturation and aggregation . LuteoliIn this study, the component target disease PPI network has 3521 nodes and 50004 connections. The core PPI network comprises 319 nodes and 9881 edges, which reflects the complex interaction between the components and their targets.G protein-coupled receptors as depicted from the results of GO analysis, which may downregulate trophoblast invasion. Studies have demonstrated [G protein-coupled receptors are key regulators of trophoblast infiltration and can be used as potential therapeutic intervention targets for pregnancy complications caused by trophoblast damage. Furthermore, studies have suggested [When performing GO and KEGG pathway analyses on the 32 potential targets obtained from the screening, the first mechanism of action of CR-RSM on the treatment of PE mainly involves nstrated  that G puggested  that GPCThe second mechanism of action of CR-RSM in the treatment of PE mainly involves the RNA polymerase II (pol II) transcription factor. The occurrence of PE is closely associated to a disorder of gene transcription. Some studies have proven that Pol II guided gene transcription regulation exhibits an ultralow expression in PE . As a trThe third mechanism of action of CR-RSM in PE therapy chiefly involves ubiquitin protein ligase. Excessive autophagy may be an important mechanism of placental dysfunction in early-onset pre-eclampsia. Some scholars , 33 beliP values were smaller in the neural active ligand receptor interaction signal pathway, Kaposi's sarcoma associated herpesvirus infection signal pathway, and osteoclast differentiation signal pathway, and they were significantly enriched. Among these pathways, the neural ligand receptor interaction signaling pathway is considered to be the most important one. The Kaposi's sarcoma associated herpesvirus contains a double stranded DNA genome and it is involved in the regulation of the expression of a variety of cyclins, apoptosis molecules, and cytokines after infection of host cells, suggesting that patients with PE may have similar pathological characteristics [In the KEGG pathway annotation analysis, the eristics . Pregnaneristics  patientsMoreover, it was discovered that the top 3 core target genes in the constructed gene pathway network of CR-RSM for PE treatment were PTGS2, MAPK14, and GSK3B. These genes are all related to placental development and placental angiogenesis. At the molecular level, NTRK1, APP, CUL3, and ESR1 are among the top 5 proteins in the degree of PPI, forming the strongest interactions with the active compounds. These interactions form a stable complex composed of the active compound and the NTRK1, APP, CUL3, and ESR1 proteins.In a nutshell, this study utilized network pharmacology and molecular docking to evaluate the complex network relationship between the multicomponents and multitargets of CR-RSM in the treatment of PE and found that the CR-RSM regimen has a potential therapeutic effect on PE. This study provides a theoretical basis for the application and further experimental research of traditional Chinese medicine in obstetrics. The mechanism may be related to downregulating the levels of AGEs-RAGE and its downstream inflammatory growth factors, weakening inflammatory response, and oxidative damage, thereby improving the vascular endothelial function Figure 8Figure 8.


Tripterygium wilfordii Hook. f. with Lysimachia christinae Hance for lung cancer, Aconitum carmichaelii Debeaux with Glycyrrhiza uralensis Fisch. in the treatment of coronary heart disease, but there is a lack of systematic quantitative analysis model and strategy to quantitatively study the compatibility rule and potential mechanism of synergism and toxicity reduction. To address this issue, we designed an integrated model which integrates matrix decomposition and shortest path propagation, taking into account both the crosstalk of the effective network and the propagation characteristics. With the integrated model strategy, we can quantitatively detect the possible mechanisms of synergism and attenuation of Tripterygium wilfordii Hook. f. and Lysimachia christinae Hance in the treatment of lung cancer. The results showed the compatibility of Tripterygium wilfordii Hook. f. and Lysimachia christinae Hance could increase the efficacy and decrease the toxicity of lung cancer treatment through MAPK pathway and PD-1 checkpoint pathway in lung cancer.Traditional Chinese medicine (TCM) usually acts in the form of compound prescriptions in the treatment of complex diseases. The herbs contained in each prescription have the dual nature of efficiency and toxicity due to their complex chemical component, and the principle of prescription is usually to increase efficiency and reduce toxicity. At present, the studies on prescriptions have mainly focused on the consideration of the material basis and possible mechanism of the action mode, but the quantitative research on the compatibility rule of increasing efficiency and reducing toxicity is still the tip of the iceberg. With the extensive application of computational pharmacology technology in the research of TCM prescriptions, it is possible to quantify the mechanism of synergism and toxicity reduction of the TCM formula. Currently, there are some classic drug pairs commonly used to treat complex diseases, such as  Wolff with Heracleum hemsleyanum Diels; Lysimachia christinae Hance with Forsythia suspensa (Thunb.) Vahl; and Coptis chinensis Franch. With Isatis afghanica Hadač and Chrtek. Among these anti-tumor drug pairs, there are also some frequently used herb pairs such as Tripterygium wilfordii Hook. f. with Glycyrrhiza uralensis Fisch., Pteris multifida Poir., and Lysimachia christinae Hance; Paeonia lactiflora Pall. With Tripterygium wilfordii Hook. f.; Aconitum carmichaelii Debeaux is mixed with Glycyrrhiza uralensis Fisch., Rheum officinale Baill., and Panax notoginseng (Burkill) F.H.Chen.Herb pairs is the simplest and most widely used prescription form in the process of treating complex diseases in TCM. The main compatibility purpose of TCM pairs is to increase effectiveness and reduce toxicity. At present, some TCM pairs are widely used in the treatment of diseases such as Tripterygium wilfordii Hook. f. (LGT) and Lysimachia christinae Hance (JQC) are one of the commonly used compatibility pairs for tumor treatment. The diterpenoids and triterpenoids of LGT and the flavonoids and polysaccharides in JQC have anti-tumor effects. Previous pharmacological studies found that the alcohol extracts of LGT and JQC had a synergistic effect on the inhibition of cell proliferation of non-small cell lung cancer. JQC combined with LGT could exert a synergistic effect and reduce the toxicity of LGT on lung cancer with the best effect at the concentration ratio of 2/1 , Traditional Chinese Medicine integrated database (http://www.megabionet.org/TCMID/) and TCM@Taiwan (http://tcm.cmu.edu.tw/zh-tw). The chemical identification and concentrations of LGT and JQC was collected from previous literature reports. All chemical structures were prepared and converted to standardized SMILES using the Open Babel Toolkit (Version 2.4.1).All chemical components of LGT and JQC were obtained from the TCM System Pharmacology Database and Analysis Platform database (TCMSP)   networks for LGT and JQC were constructed using Cytoscape software (Version 3.9.1) . The top1. Perform a rank-L Eckart–Young–Mirsky approximation of A by singular value decomposition (SVD) as 2. Estimation of The initial influence coefficient between the LGT components and the target was obtained by matrix decomposition. The matrix decomposition steps are as follows:For Re-order rows of W so that the ith column of Y has the structure Partition 3. Estimate the initial influence coefficient matrix by S = Do SVD for For the choice of L, it has been shown by published literature that we can choose L = M with good performance and superior computational efficiency . If L = Thenhttps://www.disgenet.org/) as toxicity targets for LGT.Through published literature retrieval, toxicity information of LGT was obtained, including which systems caused which specific toxic and side effects. For example, LGT has renal toxicity, which is likely to cause renal failure and renal insufficiency. The corresponding gene targets for toxic and side effects were obtained in the DisGeNET database  (https:/(1) At the beginning, (2) For all nodes x in Q, find the node t with smallest The process of component transmission to the pathogenic gene through the target involves the effective targets and toxicity targets of the component. In this study, we constructed the efficacy-toxicity network using the propagation model. The principles of the propagation model are as follows:(3) Update the value of (4) Continue the above steps until Q is an empty setTherefore, we used the model to construct Gene Transmission Chains (GTC) against LGT component targets, Protein-protein interactions (PPI) networks, and pathogenic genes of lung cancer. And finally obtaining a GTC which is transmitted to a lung cancer pathogenic gene from a LGT component target through a plurality of genes:In the GTC, we believe that the later the toxic target appears in the GTC, the less toxicity will be accumulated, and the earlier the JQC target appears, the better the synergistic effect will be. Therefore, we labeled the genes in GTC, with the component target of JQC in GTC labeled [JQC], and the toxicity target of LGT in GTC labeled [TOX]:https://portal.gdc.cancer.gov/), the correlation between the two genes was calculated and recorded as Using the lung cancer gene expression profile data obtained by The Cancer Genome Atlas (TCGA)   The number of targets of LGT component (2) Scale the scores (3) Through the common C-T network diagram of LGT-JQC, get the values of between for each component, which are denoted as (4) Final score In order to screen out the components of LGT and JQC with the strongest synergistic effect, we calculated the synergistic scores of LGT and JQC according to the following steps:Details of all LGT and JQC pairing components and scores are recorded in p-values were set at 0.05 as the cut-off criterion. The results of analysis were annotated by Pathview (https://www.bioconductor.org/).To analyze the main functions of the GTCs, Gene Ontology (GO) analysis was performed using the Diversity Visualization Integrated Database (DAVID 6.8) . And thePathview  in the R2 atmosphere. Triptolide, Perillyl alcohol and α-Terpineol (≥98% purity by HPLC) were purchased from Jingzhu Biotechnology  and dissolved in dimethyl sulfoxide .The human lung cancer cell A549 and the human hepatocyte cell L-02 were cultured in Dulbecco’s Modified Eagle’s Medium  supplemented with 10% FBS , 100 U∙mL−1 penicillin and 100 μg mL−1 streptomycin at 37°C in 5% CO3 cells per 100 μL. The next day, the culture medium was discarded and the cells were exposed to Triptolide, Perillyl alcohol and α-Terpineol at different concentrations for 0 h, 24 h, 48 h, 72 h, 96 h and 120 h, 10 μL of CCK-8  was added in the plates and cultured at 37 °C for 2 h. Absorbance at 450 nm was measured using spectrophotometer. The experiments were carried out in triplicate.Cells viability was evaluated by Cell Counting Kit-8 . Briefly, A549 cells were digested and plated into each well of a 96-well plate after adjusting the cell suspension to the appropriate concentration of 1×101,000 cells were seeded in 6-weel plates with 2 ml complete DMEM. Then, new complete DMEM containing different concentrations of drugs was added. The medium should be replaced every 3–4 days. After 2 weeks of cultivation, the supernatant was abandoned and the cells were washed with phoshate buffered saline (PBS), then fixed with methanol and stained with crystal violet  for 15 min. The numbers of colonies were counted for analysis.Cells resuspended in FBS-free medium which containing different concentrations of drugs was placed into the upper uncoated chamber for migration assay or chamber coated with matrigel  for invasion assay. All the bottom chambers were added with 20% FBS medium. Following 48 h of incubation, cells remaining in the upper membrane were removed, whereas the migrated cells were fixed with methanol and stained with crystal violet, and then counted under the microscope.Cells were collected and total protein was extracted by RIPA lysis buffer , and BCA protein assay kit  was used to determine protein concentration. Equal amount of protein samples was resolved by SDS‐PAGE gel and the proteins were subsequently moved to PVDF membrane , then the PVDF membrane were blocked  and immunoblotted with primary antibody of p44/42 MAPK (Erk1/2) , p-p44/42 MAPK (Erk1/2) , PD-L1 , GAPDH  at 4°C overnight. After washing by TBST (TBS containing 1% Tween), The membranes were exposed to corresponding secondary antibodies for 1 h. Antibody signal was detected using Clarity Western ECL substrate . The GAPDH served as an endogenous reference.Chemical component analysis plays an important role in the compatibility and the material basis research of Chinese material medica, and is the foundation of the research on the action mechanism of Chinese medicine. Through literature retrieval, we collected the high-concentration chemical components verified by HPLC and other experimental methods in LGT and JQC . The chein vitro and induces apoptosis. Among the components of JQC, perilla alcohol could sensitize lung tumor cells to apoptosis by genetic lesions present in tumor cells  network was constructed by using Cytoscape3.9.1 . The resThere were 525 shared targets in LGT and JQC , and amoin vitro and in vivo  and AKT1 (degree = 42). PTPN1 (degree = 44), a unique target of LGT has been proved to promote the proliferation and metastasis of NSCLC and high expression in lung cancer tissues . GPR37 h in vivo . These rvia increasing CXCR4 expression , also known as ERβ, it could promote lung cancer invasion pression . In addipression .In summary, these results suggested that the active ingredients between LGT and JQC may treat lung cancer through multi-target synergy, and achieve the effects of promoting efficiency and reducing toxicity after compatibility.https://cn.string-db.org/) and Cytoscape , of which 5867 genes were up-regulated and 2452 genes were down-regulated . Next, wytoscape . Modularytoscape . Then, tytoscape . In addiytoscape . Other sytoscape . AURKA iytoscape . In addiytoscape . In summLiterature retrieval and statistics showed that the most serious adverse reactions of LGT were mainly in the bone marrow and blood system, followed by the digestive system and renal system . These ain vivo in a quantitative manner. Through this model we finally obtained 1,396,561 GTCs [To better detect the gradual transfer of LGT from target to pathogenic gene during treatment, we first need to obtain the initial influence coefficients of components on the target. To solve this problem, we design a matrix decomposition model with the interaction of components and targets as well as the expression of target genes as inputs, finally we obtain a total of 10,423 component-target regulations with initial influence coefficients, based on the initial impact coefficient, we designed a new propagation model. The propagation model not only considered that the initial influence coefficient would transmit the effect to other effective targets but also to other targets related to side effects in the propagation process, so the model could reflect the cascade effect mechanism of drugs 561 GTCs . These GIn order to verify whether the constructed quantitative efficacy-toxicity network of LGT better reveals the mechanism of the combination of LGT and JQC in the treatment of lung cancer, we adopted three strategies to verify the accuracy, reliability and effectiveness of the quantitative efficacy-toxicity network of LGT. The first strategy is to observe the percentage of the number of component targets with high initial influence coefficient obtained by matrix decomposition method to all component targets of LGT. Targets with a higher initial coefficient of influence were considered to be significant targets for LGT (LGT-ST), and coverage was defined as the number of LGT-ST as a percentage of the number of targets for all components of LGT and the lung cancer pathogenic gene. The high coverage indicated that LGT-ST could retain most of the effective targets. The second strategy aims to observe and compare the number of targets for LGT and lung cancer in the screened GTSs with the number of targets for all components of LGT and pathogenic genes for lung cancer. High coverage may indicate that the GTCs retains the majority of LGT and lung cancer targets. The third strategy was mainly used to observe whether the gene enrichment pathways in the quantitative efficacy-toxicity network covered as much as possible of the gene enrichment pathways for LGT and lung cancer.We collected the lung cancer pathogenic genes reported in the published literature and database . We founThe number of LGT targets and lung cancer targets in the GTCs was counted and compared with the number collected through literature retrieval. Fortunately, 1198 LGT targets and 1192 lung cancer targets were included in the GTCs, accounting for 94% and 88% of all LGT targets and lung cancer targets . This reWe obtained the gene enrichment pathways for the efficacy-toxicity network、LGT and lung cancer from KEGG . The anaTo reveal the potential mechanism of the compatibility of LGT and JQC in the treatment of lung cancer, we conducted path enrichment analysis on the toxic targets of LGT, JQC, lung cancer, and LGT as well as related genes in the GTC. First, genes of LGT were enriched in 194 pathways, genes of lung cancer were enriched in 180 pathways, and related genes in GTC were enriched in 225 pathways, among which there were 137 common pathways, the more significant ones were MAPK signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway, cAMP signaling pathway, etc. In JQC, genes were enriched along 145 pathways, while toxicity targets for LGT were enriched along 69 pathways. We performed unified analysis on the obtained pathways of LGT, JQC, lung cancer and LGT toxicity targets, and found that the common pathway of LGT, JQC and lung cancer covered 114 pathways. These include: MAPK signaling pathway, PI3K-Akt signaling pathway, cAMP signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, Rap1 signaling pathway, etc. JQC pathways covered 42 pathways of LGT toxicity targets, including IL-17 signaling pathway, Fluid Sheet Stress and Atherosclerosis, and Human cytomegalovirus infection. These results indicate that LGT and JQC can exert the effect of treating lung cancer through multiple common pathways, and JQC also has multiple common pathways with the toxic targets of LGT , which mTo further analyze the important pathways of the compatibility of LGT and JQC in the treatment of lung cancer, we constructed a target-pathway (T-P) network for common pathways that covered more targets, including pathways related to adverse reactions . The T-PThrough published literature retrieval, we found that among the common pathways, MAPK pathway, PI3K-Akt pathway and PD-L1 expression and PD-1 checkpoint pathway in cancer had the highest correlation with lung cancer; therefore, we selected MAPK pathway, PI3K-Akt pathway, and PD-L1 expression and PD-1 checkpoint pathway in cancer to elaborate the detailed mechanism of LGT and JQC in the treatment of LC. First, we constructed an integrated signaling pathway by integrating the three pathways. The component targets of LGT and JQC were then mapped to an integrated signaling pathway . The resIn addition, we have found that the IL-17 pathway in the toxicity target enrichment pathway plays a key role in the pathological process of a variety of inflammatory reactions and autoimmune diseases, including the toxic and side effects of a variety of LGT such as acute renal failure and liver dysfunction. JQC covered multiple pathways related to toxicity targets including IL-17 pathway, which also indicated that JQC participated in the regulation of toxicity-related pathways such as IL-17 pathway to achieve the effect of reducing toxic and side effects on LGT. We mapped the JQC targets and the LGT toxicity targets onto the IL-17 signaling pathway  to discuin vitro. A549 cell was treated with triptolide (12.5 nM), perillyl alcohol (500 μM) and α-terpineol (500 μM) alone or in combination. As shown in To further validate the reliability of the possible mechanisms of promoting efficiency of LGT and JQC in the treatment of lung cancer, the human lung cancer cell A549 was used for experiment verification in vitro. L-02 cell was treated with Triptolide, Perillyl alcohol and α-terpineol alone or in combination. As shown in In addition, to validate the reducing toxicity effect of LGT and JQC in the treatment of lung cancer, the human hepatocyte cell L-02 was used for experiment verification via multi-components, multi-targets and multi-pathways, and the main purpose of compatibility in formula is to promoting efficiency and reducing toxicity. As the simplest form of compatibility of TCM, herb pair is widely used in the treatment of complex diseases. Herb pair, targets and pathogenic genes form a complex intervention network. How to find the most effective intervention relationship in this intervention network and the underlying mechanisms of promoting efficiency and reducing toxicity between LGT and JQC are the keys to understand the material basis and molecular mechanism of the Chinese herb pair, and also the basis for the secondary development of TCM. At present, the research on TCM based on network pharmacology mainly focuses on decoding the potential mechanism of the efficacy of prescriptions. Through optimal model, the herbs and components with good intervention effect can be screened out, and the herbs and components with antagonistic effect and even side effect are removed, so that the herb pairs or the prescriptions is simpler and more effective (1. Network pharmacology has established a fixed analytical step in the analysis of therapeutic mechanisms. In this rule, the first step is to collect the components of the plant drugs, do ADMET screening to select the active components, then predict the target and deduce the molecular mechanism. This flowchart really solves the molecular mechanism of some formulas of TCM in treating complex diseases. Such as: Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model , Computa2. The second step is to identify the toxicity targets from the active ingredient prediction targets, and further screen through the literature reports to retain the significant toxicity targets. However, there are also exist two problems. One is the clutter and interference of component target networks. The other is that most network pharmacology analyses ignore that the intervention of components is a cascade transmission process, specifically refers to the transmission of the intervention effect from target genes to pathogenic genes. In order to solve these two problems, we have adopted some new strategies. In the first strategy, the matrix decomposition method is used to calculate the initial influence coefficient of the component targets. Through the verification of this method, we have found that the component targets with high initial influence coefficient obtained by this method cover the majority of significant component targets of LGT, and have high coverage for the functional pathways of LGT. In the second strategy, considering that the intervention of component targets could be transmitted to the pathogenic genes through PPI network, we constructed a complex network of component-target-pathogenic genes. The network takes into account the presence of both LGT toxicity targets and JQC targets and includes the effects of the propagation. Based on this model, we constructed an efficacy-toxicity network consisting of LGT and JQC component targets, LGT toxicity targets, lung cancer pathogenic genes, and PPI network.In the use of TCM, the formulas play important roles in the treatment of complex diseases ffective . Compatiffective . HoweverThrough the verification of target and pathway coverage, we also found that some ineffective or weak GTCs were removed, and the significant GTCs covered most of the functional targets, further proving the effectiveness of the efficacy-toxicity network we constructed. In the efficacy-toxicity network, multiple cascade GTCs exist in the same cascade signal module. This module mainly controls the downstream genes such as CFL1, MAP2K1, ACTB, PTBP1, CSNK2A2, PPIA, KDM2A, and RAF1 to treat lung cancer through the cascade reaction of DHCR24-UBC. In this module, the first gene, DHCR24 is capable of resisting oxidative stress-induced apoptosis by scavenging hydrogen peroxide and plays a vital role in the antioxidant/anti-inflammatory cellular signaling pathway . As an iBased on the propagation models of network toxicology and network pharmacology, we designed an integrated model of efficacy and toxicity which based on matrix decomposition and effect propagation, to detect the possible mechanisms of promoting efficiency and reducing toxicity of LGT and JQC in the treatment of lung cancer. Compared with other published studies, this study specifically reported the initial influence coefficients of drug component targets obtained by matrix decomposition and the construction of quantitative efficacy-toxicity network based on propagation model, which fully considers that the intervention effect of the TCM components is a cascade transmission process. Our research is a computational mining work based on pharmacological basic data, which provides a feasible scheme to reduce the verification scale for the experiment. The accurate application of this method is expected to provide a theoretical reference for the compatibility law of TCM prescriptions.However, this study also has some limitations. First of all, we should select more targets with significant initial influence coefficients from the targets of LGT components to verify the reliability of the matrix decomposition method. In addition, the efficacy-toxicity network of component-target-pathogenic gene we constructed ignores the path loss that may occur during gene transmission. In future studies, we hope to further improve the model and try to eliminate the effect of path loss in the gene transfer process on the final result.