Finally, we demonstrate that these enzymes can degrade ethyl-paraoxon down to sub-inhibitory concentrations of acetylcholinesterase, confirming their efficacy from high to micromolar doses.Organophosphorus nerve agents (OPNAs) are highly toxic compounds inhibiting cholinergic enzymes in the central and autonomic nervous systems and neuromuscular junctions, causing severe intoxications in humans. Medical countermeasures and efficient decontamination solutions are needed to counteract the toxicity of a wide spectrum of harmful OPNAs including G, V and Novichok agents. Here, we describe the use of engineered OPNA-degrading enzymes for the degradation of various toxic agents including insecticides, a series of OPNA surrogates, as well as real chemical warfare agents . We demonstrate that only two enzymes can degrade most of these molecules at high concentrations (25 mM) in less than 5 min. Using surface assays adapted from NATO AEP-65 guidelines, we further show that enzyme-based solutions can decontaminate 97.6% and 99.4% of 10 g∙m Organophosphorus chemicals (OPs) are highly toxic compounds inhibiting cholinesterase enzymes from the central nervous system and causing severe poisoning in humans ,2. They Given the toxicity of OPs, particularly OPNAs, decontamination methods and medical countermeasures have been developed to counteract their poisoning effects ,24,25,26This study aims to demonstrate (i) that enzyme-based formulations can be used to decontaminate a broad spectrum of nerve agents including the poorly studied Novichok agents and (ii) that such formulations can be used to degrade high concentrations of neurotoxic chemicals used in solution or spread on surfaces. To this end, we evaluate the potential of two engineered PTEs, namely GG1 and GG2, developed by the company Gene&GreenTK ,45. We fcat/KM values above 107 s−1∙M−1, which is in the same order of magnitude as previously reported for potent OP-degrading enzymes  was tested, and the performance of the enzyme solutions was evaluated by determining half-life (t1/2) values  in combination with the enzymes (20 µM) in Tris buffer . The higher concentration of agent facilitated the monitoring of the reactions with ) values . AdditioKm value .Although GG1 and GG2 performed comparably in the degradation of G-agent surrogates, GG2 performed better than GG1 with CM Cyclosarin. Therefore, GG2 was chosen for experiments with the live G-agents. Conversely, as GG1 showed a better performance with the V-agent surrogates than GG2, the former was used in the experiments with VX.31P NMR and LC-MS analysis. Agent degradation occurred through hydrolysis of the P-F bonds in G-agents and the P-S bond in VX, respectively. It is important to emphasise that P-OEt scission in VX, resulting in the highly toxic agent E2192, was not observed. Inspection of the 31P NMR spectra of the control curves revealed that, besides spontaneous hydrolysis, the G-agents formed adducts with the buffer molecules [a–d showsolecules , which cTo further evaluate the performance of the enzyme solutions in relation to the various G- and V-agents, additional experiments were executed. The hydrolysis profiles of VX (25 mM) exposed to serial dilutions of the GG1 enzyme solution were determined . The res1/2 2–3 min). Tabun, however, showed a step hydrolysis in the first couple of minutes (65% tabun remaining after 4 min) followed by slower hydrolysis that was reminiscent of the rate of degradation in the control , it became evident that this enzyme was comparably reactive towards most of the G-agents used . Sarin wM, thus allowing us to estimate kcat  product in each case was formed by hydrolysis of the P–F bond, giving compounds (1a) for A230, (1b) for A232 and (1c) for A234 (1a) to methylphosphonic acid (2). To evaluate whether this secondary reaction can be ascribed to the enzyme activity (competitive substrate), to spontaneous hydrolysis or both, the enzymes were removed by centrifugation over a molecular weight cut-off filter after 22 min of reaction, and the evolution of the reaction mixture was followed by NMR. Interestingly, concentrations of (1a) and (2) remain unchanged after enzyme removal, suggesting that conversion of (1a) to (2) is enzymatically catalysed  of VX and soman, according to the NATO AEP-65 performance requirements  suggesting that decontamination was mainly driven by the buffer washing effect. Nevertheless, analysis of the run-off showed the absence of soman (31/38 ppm) and only the presence of hydrolysed soman (26 ppm), while a large fraction of intact soman was detected in the run-off of the buffer-only decontamination. Regarding VX, high surface decontamination efficacies were observed both in the presence and absence of enzyme . Similarly, no residual VX (62 ppm) was found in the run-off, but only the hydrolysis product (26 ppm). By contrast, VX remained fully intact in the run-off in the absence of enzyme. While OPNAs degrading PTE were mainly considered for developing prophylactic approaches and medical countermeasures, our results underline that they are also of outmost interest for external decontamination purposes and would deserve to be further considered in this way to provide sustainable and non-toxic decontamination solutions for OPNAs.To further address the potential of the two enzymes for decontamination purposes, panels painted with chemical agent resistant coating (CARC) were contaminated with high amounts  values of 3.87 ± 0.33 × 107 and 1.46 ± 0.33 × 107 were determined for GG1 and GG2, confirming previous results obtained by following p-nitrophenolate release during ethyl-paraoxon hydrolysis. In addition to our evaluations regarding high concentrations of OPNA, the results obtained here suggest that GG1 and GG2 enzymes are able to degrade very low doses of ethyl-paraoxon down to sub-inhibitory concentrations of rHAChE.Alongside decontamination experiments involving high concentrations of agents, further assays were performed to demonstrate the potential of these enzymes to degrade OPs to innocuous doses. Acetylcholinesterase inhibition assays, using a recombinant variant of human acetylcholinesterase (rHAChE) expressed in erformed ,51. OPs 1H NMR).Ethyl-paraoxon was purchased from Sigma-Aldrich, St. Louis, MO, USA . Coumaric derivatives of cyclosarin, sarin, soman, tabun, VX and DEVX  were synthesised on demand by Enamine Ltd. . Soman, tabun, cyclosarin, sarin, VX, A230, A232 and A234 were synthesised in-house . The compounds were >95% pure (determined using quantitative Brevundimonas diminuta PTE (P0A434) [E. coli BL21(DE3)-pGro7/GroEL (TaKaRa) chaperone expressing strain. The starter and culture were produced in a ZYP auto-inducible medium 2SO4, 100 mM KH2PO4, 100 mM Na2HPO4, 0.5% (w/v) glycerol, 0.05% (w/v) glucose, 0.2% (w/v) α-lactose) supplemented with ampicillin (100 µg∙mL−1) and chloramphenicol (34 µg∙mL−1). Cells were grown at 37 °C and stirred until OD600 nm reached 0.8–1, then induction was performed by addition of L-arabinose (0.2% (w/v)) and CoCl2 (0.2 mM). At the same time, the temperature was reduced to 16 °C. After 20 h of growth, cells were harvested by centrifugation , resuspended in PTE lysis buffer  and stored at −80 °C. Cells were lysed by sonication ; Amplitude 40) and centrifuged . Crude lysates were used with activities around 450–1100 U∙mL−1 for GG1 and 6000–25,000 U∙mL−1 for GG2 on ethyl-paraoxon. When needed, recombinant PTEs, with Strep-TEV tag, were purified by injection on StrepTrap column : ÄKTA Avant). Protein concentration was measured with a NanoDrop 2000 spectrophotometer , and protein purity was assessed by SDS-PAGE.GG1 and GG2 were engineered from (P0A434)  and were(P0A434) . In shorCatalytic parameters were measured at 25 °C in triplicate using 96-well plates with a reaction volume of 200 µL. Reactions were recorded by a microplate reader  in a 6.2 mm path length cell and using the Gen5.1 software. All the kinetic assays were performed in PTE activity buffer .−1∙cm−1). Chlorpyrifos (within 0.05 and 1 mM) hydrolysis was followed at 310 nm (ε = 5562 M−1∙cm−1). Malathion (within 0.1 and 5 mM) and DEVX (within 0.01 and 2 mM) hydrolysis were monitored at 412 nm (ε = 14150 M−1∙cm−1) by the addition of 5,5’-dithiobis-2-nitrobenzoic acid (DTNB) to the reaction mixture . Graph-Pad Prism 6 software was used to obtain the catalytic parameters by fitting the data to the Michaelis-Menten (MM) equation.Ethyl-paraoxon (within 0.01 and 2 mM) and ethyl-parathion (within 0.05 and 1 mM) hydrolysis were monitored at 405 nm . We assumed that  kcat/KM .For OPNAs, only Caution: OPNAs are extremely toxic and must be used by trained personnel in a facility that has been authorised to use these agents.31P NMR) nerve agent degradation experiments. A typical experiment was conducted as follows. Water (1.0 mL 10% D2O/H2O) was added to a vial containing the lyophilised buffer/enzyme mixture and shaken until all solids were dissolved giving 0.7 mg∙mL−1 of enzyme . This solution is referenced as the undiluted concentration. Dilutions of enzymes were obtained by mixing Tris buffer in 10% D2O/H2O with the enzyme stock solution, until the desired dilution was obtained. Pure agent  was weighed in a 4 mL vial and an appropriate amount of the buffer/enzyme stock solution and 10% D2O/H2O was added to give a total concentration of 25 mM agent.A Bruker Avance III 400 MHz spectrometer was used to monitor  of agent in acetonitrile were used instead of neat agent. Thus, 30 µL of agent stock solution was mixed with 570 µL of enzyme stock, giving 25 mM agent concentration and 5% acetonitrile in the reaction mixture.The mixed GG1/GG2 experiments with Novichok agents were performed by mixing 30 µL of agent stock solution, and 285 µL of both enzyme stock solutions.31P NMR measurements were started as soon as possible, using the standard 31P{1H} pulse sequence and 64 scans per measurement. As a result of locking and shimming, the first measurement commenced after 4 min, and subsequent measurements took 3 min each, up to a total time of about one hour (20 measurements). The integrals of the agent and its degradation products were determined, and their sum was set to 100%, enabling representation of degradation of the agent or formation of the hydrolysis products as a fraction of the total phosphorus content. All degradation experiments were performed at least in duplicate.Directly after combining the agent and the enzyme(s), the mixture was vortexed for 10 s and transferred to an NMR tube. Sequential LC-MS experiments were performed on a Waters HPLC system connected to a Waters QDA mass spectrometer . Samples were diluted appropriately to prevent overloading of the column. The column was a Cortes-T3 4.6 mm × 100 mm, 2.7 µm  with a gradient of 0–100% solution B in A). A: 5% acetonitrile + 0.2% formic acid; B: 95% acetonitrile + 0.2% formic acid; gradient: 1 min 0% B, then a gradient to 100% B in 8 min.−1 was used.Alternatively, a Phenomenex Kinetex biphenyl 4.6 mm × 150 mm, 2.6 µm  column was used, employing the same buffers except that 0.1% TFA was used instead of formic acid. Gradient: 1 min 0% B, then to 100% B in 12 min. Generally, a flow of 1.0 mL∙minE. coli Origami B cells. Starter and culture were produced in 2xYT medium  supplemented with ampicillin (100 µg∙mL−1). Culture was grown at 37 °C with agitation until an OD600 nm of 1 was reached, then isopropyl β-d-1-thiogalactopyranoside  was added and the temperature was reduced to 16 °C. After 24 h of growth, cells were harvested by centrifugation . Cells were resuspended in rHAChE lysis buffer  glycerol and 0.25 mg∙mL−1 lysozyme) and stored at −80 °C. Lysate was sonicated  and centrifuged , octyl glucoside 0.1% (w/v) was added. A first ammonium sulfate precipitation was performed, saturation from 0% to 40% for two hours at 4 °C. After centrifugation , a second ammonium sulfate precipitation was performed, saturation from 40% to 50% overnight at 4 °C. After centrifugation , the pellet was resuspended in activity buffer  glycerol and 0.1% (w/v) octyl glucoside). rHAChE was injected in desalting column , to remove ammonium sulfate, then in exclusion size chromatography . rHAChE activity was determined using Ellman’s reagent  and acetylthiocholine (2.5 mM), and reaction was followed at 412 nm for 10 min with a microplate reader  [−1.Plasmid coding for rHAChE, pET32b-rHAChE-3G4, was kindly provided by Moshe Goldsmith from the Weizmann Institute . As previously described , pET32b-VT, USA) . Fractiowww.proqares.com). Metal panels  were coated with (Dutch) chemical agent resistant coating (CARC), according to the Dutch army painting protocol, by van Geffen BV, Tilburg, the Netherlands. The coating was applied on all sides of the panels. In each experiment, a total of 12 panels were used  and one negative control .These experiments were conducted in collaboration with Proqares (−1) in Tris buffer . A 1 M HCl solution was freshly prepared (“quenching solution”). The panels were conditioned to ambient conditions for at least 24 h prior to testing. Agent (VX or GD) was applied to the panels ). Moreover, 11 CARC panels  were contaminated and incubated for 15 min at 20 °C. Three panels were decontaminated by submerging each panel for 15 min in 20 mL “decontaminant” and three panels were decontaminated with “buffer”. One uncontaminated panel was also decontaminated with “decontaminant” (negative control). The five remaining contaminated panels served as positive controls.The decontamination solution (“decontaminant”) was prepared by dissolving enzyme  of each of the three “decontaminant” experiments and two samples (≈2 mL each) of each of the three used “buffer” experiments were collected directly after decontamination. HCl (1 M) was added in 1 of each pair of samples until the pH reached 5–6 (quenching enzyme activity). These samples were filtered, D-1). Quantitative data were calculated using a calibration curve. The amount of agent found on a panel was calculated by the sum of the amounts of agent found in the two consecutive extractions.The decontaminated panels were briefly rinsed with water and dried with adsorbent paper without rubbing. Next, all panels were extracted twice with 10 mL of diethyl succinate for 90 min. The amount of agent in each extract was quantified by GC-FPD . Temperature programmes—GD: isothermal at 160 °C; VX: 0.4 min at 170 °C, followed by a temperature gradient to 195 °C (50 °C∙min−1). Finally, rHAChE activity was measured using Ellman’s reagent  and acetylthiocholine (2.5 mM). The reaction was monitored at 412 nm for 10 min with a microplate reader  [Inhibition assays were carried out as previously described ,51. FirsVT, USA) . Curves In this paper, two engineered PTEs were evaluated for their hydrolytic potential towards OPNAs, with the aim of developing an environmentally benign, non-corrosive and effective formulation for surface decontamination. Several representative examples of G-agents, VX as a representative V-agent and three Novichok agents were tested with these enzymes. The kinetic results clearly demonstrated the potential for rapid degradation of G- and V-type agents. These enzymes were also able to degrade Novichok compounds albeit with lower overall hydrolysis rates as compared with G- and V-agent hydrolysis. However, the use of a mixture of both enzymes, under the same conditions, turned out to completely destroy A230 and A232 as well as the majority of A234, showing that these enzymes can effectively work in concert and that they preferentially target a different one of the two enantiomers of each agent. This finding will be useful for future engineering and further optimisation of enzyme activity. Preliminary surface decontamination experiments, following NATO’s guided protocols, clearly indicate that crude enzymatic solutions show promise in the cost-effective decontamination of surfaces contaminated with nerve agents. Furthermore, these enzyme-based innocuous solutions may also be of prime interest for skin decontamination purposes and are deserving of further study.


Lactobacillus and lower Proteobacteria, Escherichia–Shigella, and Clostridium_sensu_stricto_1 after transportation. As a result, the TS+GA group had the highest total short-chain fatty acids and acetic acid. Also, the fecal and serum metabolomics analyses revealed that GA markedly reversed the abnormalities of amino acid metabolism, lipid metabolism, carbohydrate metabolism, and nucleotide metabolism caused by stresses. Finally, Spearman’s correlation analysis was carried out to explore the comprehensive microbiota and metabolite relationships. Overall, dietary supplementation of GA alleviates oxidative stress and inflammatory response in stressed puppies by causing beneficial shifts on gut microbiota and metabolites that may support gut and host health.Early-life exposure to environmental stress disrupts the gut barrier and leads to inflammatory responses and changes in gut microbiota composition. Gallic acid (GA), a natural plant polyphenol, has received significant interest for its antioxidant, anti-inflammatory, and antimicrobial properties that support the maintenance of intestinal health. To assess whether dietary supplementation of GA alleviates environmental stress, a total of 19 puppies were randomly allocated to the following three dietary treatments for 2 weeks: 1) basal diet (control (CON)); 2) basal diet + transportation (TS); and 3) basal diet with the addition of 500 mg/kg of GA + transportation (TS+GA). After a 1-week supplementation period, puppies in the TS and TS+GA groups were transported from a stressful environment to another livable location, and puppies in the CON group were then left in the stressful environment. Results indicated that GA markedly reduced the diarrhea rate in puppies throughout the trial period and caused a moderate decline of serum cortisol and HSP-70 levels after transportation. Also, GA alleviated the oxidative stress and inflammatory response caused by multiple environmental stressors. Meanwhile, puppies fed GA had a higher abundance of fecal Firmicutes and  Stress response is a ubiquitous physiological response elicited when the threat to the homeostasis is perceived by the organism due to environmental, physical, or psychological stimuli . Early-lLactobacillus and Bifidobacterium are the main genera of probiotic bacteria, which enhance the host immune system and favorably modulate gastrointestinal physiology  –19. The ysiology , 24. Morbacteria –28 becaubacteria –31. Convammation , 33. It ammation , 18. Colvia the modulation of colon microbiota composition  and were performed following the guidelines of the Laboratory Animal Center at the South China Agricultural University. Animal welfare was monitored by research and animal care staff daily.A total of 19 beagle dogs Table 1 ad libitum. GA (purity > 99%) was purchased from Wufeng Chicheng Biotech Co., Ltd . The dose of GA supplemented was based on previous studies  under a constant temperature and humidity  with a light/dark cycle of 12 h. All dogs were continued on their respective diets for another week and given access to toys for behavioral enrichment at all times and to exercise outside of their cages and socialize with each other or humans at least once a day. The study design is depicted in After 4 weeks of adaptation to a basal diet, these puppies were randomly allocated to one of the three dietary treatments: 1) basal diet , 2) basal diet , and 3) basal diet with the addition of 500 mg/kg of GA (TS+GA group). The experimental period was 14 days including 7 to 1 days before transportation (BT7–BT1) and 1 to 7 days after transportation (AT1–AT7). Puppies in the TS and TS+GA groups were exposed to the road transportation for 3 h (from 14:00 to 17:00) at a speed range of 50Throughout the trial period, a 200-g basal diet was collected weekly and was kept in the refrigerator at −20°C. Feed samples were dried in the oven and were ground through a 1-mm screen for chemical composition analysis. The dry matter (DM) and organic matter (OM) were determined for the diets according to AOAC  . Acid-hy2, and stored at −80°C until DNA extraction. Finally, an aliquot for metabolomics analysis was snap-frozen on liquid N2 and stored at −80°C until analysis.During the whole experimental period of 2 weeks, fecal scores (FS) described by Middelbos et al.  were ass×g at room temperature for 15 min. After centrifugation, the supernatants were aliquoted into microcentrifuge tubes and stored at −80°C for further analysis. Serum glutathione peroxidase (GSH-Px), malondialdehyde (MDA), total antioxidant capacity (T-AOC), and superoxide dismutase (SOD) were detected using commercial kits  according to the manufacturer’s protocol. Serum COR, GC, ACTH, HSP-70, immunoglobulin G (IgG), tumor necrosis factor-alpha (TNF-α), interferon-γ (IFN-γ), and interleukin 4 (IL-4) were measured using commercial ELISA kits . Finally, an aliquot for serum metabolomics analysis was snap-frozen on liquid N2 and stored at −80°C until analysis.On BT1, AT1, and AT7 after overnight fasting, a 5-ml blood sample was collected from each dog by forelimb vein and left to stand for 30 min before centrifugation at 3,500® High-Fidelity PCR Master Mix (New England Biolabs) with 2 µM of forward and reverse primers and about 10 ng of template DNA. Thermal cycling consisted of initial denaturation at 98°C for 1 min, followed by 30 cycles of denaturation at 98°C for 10 s, annealing at 50°C for 30 s, and elongation at 72°C for 30 s, followed by 72°C for 5 min. The same volume of 1× loading buffer (contained SYB green) was mixed with PCR products (in equidensity ratios) and then operated with electrophoresis on 2% agarose gel for detection. Then, the mixture of PCR products was purified with Qiagen Gel Extraction Kit . Sequencing libraries were generated using the TruSeq® DNA PCR-Free Sample Preparation Kit  following the manufacturer’s recommendations, and index codes were added. The library quality was assessed on the Qubit@ 2.0 Fluorometer (Thermo Scientific) and Agilent Bioanalyzer 2100 system. At last, the library was sequenced on an Illumina NovaSeq platform, and 250-bp paired-end reads were generated.On BT1, AT1, and AT7, fresh fecal samples were collected from the pen floor of each dog within 15 min of defecation. Total genome DNA from fresh fecal samples was extracted using the cetyltrimethylammonium bromide method. DNA concentration and purity were monitored on 1% agarose gels. According to the concentration, DNA was diluted to 1 ng/µl using sterile water. 16S rRNA genes of 16S V3–V4 were amplified using the primers 341F (5′-CCTAYGGGRBGCASCAG-3′) and 806R (5′-GGACTACNNGGGTATCTAAT-3′) with the barcode. All PCRs were carried out with 15 µl of Phusionhttp://ccb.jhu.edu/software/FLASH/) (http://qiime.org/scripts/split_libraries_fastq.html) (https://www.arb-silva.de/) using the UCHIME algorithm   . Quality/FLASH/)  accordintq.html)  quality-go.html)  to detecgo.html) . Then thhttp://drive5.com/uparse/) (http://www.arb-silva.de/) (http://www.drive5.com/muscle/) (http://huttenhower.sph.harvard.edu/lefse/). Correlation Network was performed using the OmicStudio tools at https://www.omicstudio.cn/tool. Function prediction of bacteria was conducted using PICRUSt (http://picrust.github.com/picrust/).Sequences analyses were performed by Uparse software  . Sequenclva.de/)  was usedmuscle/)  to studytert-butyl ether was added, and the vortex was continued for 5 min, and the supernatant was further centrifuged at 14,000 rpm for another 10 min at 4°C to remove the precipitation. Finally, the upper extraction solution was harvested and filtered through 0.22-µm Millipore pore membrane filters to a 2-ml sample vial. Samples were stored at −20°C until gas chromatography–MS (GC-MS) analysis. All steps above were performed at 4°C or on ice.The fresh fecal samples collected on BT1, AT1, and AT7 were pretreated, and extraction of SCFAs and BCFAs was performed as follows. The frozen stool samples were placed on ice to thaw, and a 0.2-g fecal sample was added with 1 ml of ultra-pure water. After vortex for 2 min, the samples were sonicated in an ice bath for 10 min and then centrifuged at 14,000 rpm for 10 min at 4°C. The supernatant was promptly transferred to a 2-ml centrifuge tube, and then a total of 20 μl of 25% metaphosphoric acid solution and 0.25-g anhydrous sodium sulfate were added to acidification and salting out, respectively. After vortex for 2 min, 1 ml of methyl The quantitative analysis of SCFAs and BCFAs was carried out using the GCMS-QP2020 system . The gas chromatography was equipped with an auto-injector AOC-20i (Shimadzu) and coupled to a flame ionization detector. The chromatographic separation was performed on a DB-FFAP capillary column (30 m × 0.25 mm × 0.25 μm). Sample (0.6 μl) was injected with a 30:1 split ratio using an autosampler. The injection port was set to a temperature of 250°C. The initial temperature of the column was 80°C for 2 min and increased to 150°C at a rate of 10°C/min for 2 in, and to 180°C at a rate of 15°C/min for 5 min. The total run time was 18 min. Helium  was the carrier gas with a flow rate of 3 ml/min. The MS parameters were electron impact mode at ionization energy of 70 eV. The ion source and interface temperatures were 230°C and 250°C, respectively. The solvent delay time was 1 min, 230°C. The acquisition mode was selected at ion monitoring mode with a scan interval of 0.3 s.The fresh fecal and serum samples collected on BT1, AT1, and AT7 were processed as described previously  with slihttps://www.metaboanalyst.ca) was used to perform multivariate analysis. Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) of metabolites were performed. Pathway enrichment analysis was performed by using the enrichment analysis module on MetaboAnalyst 5.0. The visualization results of the models were obtained with MetaboAnalyst 5.0.UPLC-Orbitrap-MS/MS analysis method was carried out as described previously , with mip < 0.05, and tendencies were at p < 0.10. To preliminarily screen the differential metabolites, we selected the metabolites that had a p-value of less than 0.05  and a variable importance in projection (VIP) score greater than 1.0 . Spearman’s correlation values and significance were computed with the R version 3.6.1. Clustering correlation heatmap with signs was performed using the OmicStudio tools at https://www.omicstudio.cn.SPSS 26.0 and GraphPad Prism 8.0 software were used for statistical analysis and graphical presentation. One-way ANOVA followed by the multiple range test of least significant difference was used to determine the statistical significance of multiple comparisons. All data were expressed as the mean ± standard error (SE). Significant differences were at p < 0.01), BT3 (p < 0.05), and BT1 (p = 0.085). And we found that FS increased in the TS group on AT1 (p = 0.085) and AT2 (p < 0.05). During the whole experimental period (p < 0.001). Total diarrhea rate (TDR) in the CON, TS, and TS+GA groups were 26.5%, 22.6%, and 4.1%, respectively, and GA reduced TDR by as much as 84.5% and 81.9% compared with the CON and TS groups, respectively.Changes in FS are shown in p = 0.06, p < 0.01; p < 0.05), and puppies fed GA had no significant change as compared with the TS group.Puppies fed a diet containing 500 mg/kg of GA for 7 days had a trend toward lower COR compared with the CON group (p = 0.057). Dietary GA supplementation markedly improved the GSH-Px activity after transportation (p < 0.01). Additionally, the TS group had a marginally higher MDA level than the CON group on AT1 , and the TS+GA group had a decreasing MDA level over the CON group on AT7 (p < 0.05). The T-AOC and SOD contents had no obvious change among groups .There was no different GSH-Px activity between the CON and TS groups on BT1 and AT1 . Though both the CON and TS+GA groups had surprisingly higher TNF-α levels than the TS group on BT1 , and no significant difference was observed between the TS+GA and TS groups. Similarly, the TS and TS+GA groups showed an unexpected increase in IFN-γ level over the CON group on BT1 .The TS group tended to decrease the serum IgG level on AT1 relative to the CON group , especially that puppies fed the dietary supplementation of GA had distinct separation over the TS group (p < 0.05).On BT1, puppies fed a basal diet at 500 mg/kg of GA for 7 days had more Observed_species and higher Chao1 and ACE indices than those of the CON group (p = 0.055). Furthermore, GA caused inhibition of Proteobacteria growth induced by transportation stress (p < 0.05). Also, the most abundant families included Erysipelotrichaceae (23.28%), Peptostreptococcaceae (12.53%), Lachnospiraceae (12.22%), Bifidobacteriaceae (11.36%), Peptostreptococcaceae (7.18%), Lactobacillaceae (6.60%), and Fusobacteriaceae (6.52%) at various phases. Decreasing Peptostreptococcaceae abundance was observed in the TS+GA group compared with the CON group on AT1 (p < 0.05). In contrast, a relative abundance of Lactobacillaceae was higher in the TS+GA group compared with the CON group on AT1 (p < 0.05). Relative abundance of Eggerthellaceae in the TS group significantly increased over the CON group, and the TS group had a higher Eubacteriaceae abundance than the CON and TS+GA groups (p < 0.05). Finally, the most abundant genera were Allobaculum (16.08%), Bifidobacterium (11.36%), Peptoclostridium (11.08%), Blautia (8.48%), Lactobacillus (6.60%), Turicibacter (5.26%), Cetobacterium (4.40%), Escherichia–Shigella (2.46%), Streptococcus (2.33%), Fusobacterium (2.08%), Collinsella (1.67%), and Faecalibacterium (1.27%). Relative abundance of Romboutsia significantly decreased in the TS+GA group compared with the CON group on BT1. Relative abundances of Lactobacillus and Faecalibaculum were higher, and relative abundances of Escherichia–Shigella and Clostridium_sensu_stricto_1 were lower in the TS+GA group compared with the CON or TS group on AT1 (p < 0.05). The TS group had a higher relative abundance of Allobaculum and Dubosiella than the CON group on AT7 (p < 0.05), while no difference was observed in the TS+GA group; and both the TS and TS+GA groups had lower Turicibacter relative to the CON group (p < 0.05).The most abundant phyla included Firmicutes (60.24%), Actinobacteria (11.47%), Fusobacterota (6.52%), Actinobacteriota (3.52%), Proteobacteria (3.24%), and Bacteroidota (1.13%) at various time points  pathway using 16S rRNA data. On BT1, puppies fed GA had more abundant amino acid metabolism, energy metabolism, carbohydrate metabolism, nucleotide metabolism, metabolism of cofactors and vitamins, and metabolism of terpenoids and polyketide  and isovaleric acid (p < 0.05) content relative to the CON group on AT1. Similarly, the TS+GA group had a similar trend of increase in total SCFAs to the CON group .No significant differences in SCFAs concentrations were observed among the three groups except for total BCFAs between the CON and TS groups on BT1 , carbohydrate metabolism (glyoxylate and dicarboxylate metabolism), energy metabolism (nitrogen metabolism), and nucleotide metabolism (pyrimidine metabolism) between the CON and TS groups , and the total SCFAs (acetic acid and propionic acid) had a weak positive association with Firmicutes. On AT7, uridine diphosphate-N-acetylglucosamine was negatively correlated with the relative abundance of Turicibacter. Furthermore, butyric acid and isobutyric acid had a weak positive association with the allobaculum.Spearman’s correlation analysis was performed for the differential feces and serum metabolites and fecal microbiota obtained by high-throughput 16S rRNA sequencing. On AT1, we found that fecal l-lactic acid, oleic acid, and spermidine were positively correlated with Clostridium_sensu_stricto_1 on AT1. Likewise, alpha-linolenic acid, l-lactic acid, and oleic acid were also positively correlated with Escherichia–Shigella. And a significant positive association was found between l-lactic acid with Proteobacteria. In contrast, alpha-linolenic acid, oleic acid, and spermidine were negatively correlated with Lactobacillaceae and Lactobacillus. Additionally, strong negative and positive associations of the l-arginine with Faecalibaculum and the arachidonic acid with Firmicutes were observed. On AT7, serum phytosphingosine and taurochenodeoxycholic acid had a reverse association with Eggerthellaceae. Similarly, glyceraldehyde and l-carnitine had positive and negative associations with Turicibacter. And dodecanoic acid and homovanillic acid were positively correlated with Eubacteriaceae.As shown in Escherichia–Shigella throughout the experiment. Unexpectedly, FS in the TS group fluctuated considerably before transportation, whose reason may be the large individual differences for all puppies in response to the stressful environment. A previous study conducted by Cai et al.  and Lactobacillaceae (Lactobacillus) after transportation. Fecal BCFAs  are generated by microbial fermentation of branched amino acids, valine, leucine, and isoleucine , xanthine, adenosine, xanthosine, uric acid, phosphoglycolic acid (carbohydrate metabolism), tetrahydrodeoxycorticosterone, and glyceraldehyde (lipid metabolism) were upregulated due to the GA treatment. We considered them as the biomarkers for evaluating the influence of dietary GA treatment on fecal metabolites in puppies.Microbiota-derived metabolites, often secreted in the intestine and translocated across the intestinal barrier into the circulating system, are very important modulators for host metabolism , 103. InO-Methygallic acid (4-OMeGA) is the primary metabolite of GA in human plasma and urine , citric acid, l-lactic acid, glyceraldehyde (carbohydrate metabolism), alpha-linolenic acid, oleic acid, linoleic acid, arachidonic acid, 13-l-hydroperoxylinoleic acid, chenodeoxycholic acid, taurine, cholic acid, taurochenodeoxycholic acid (lipid metabolism), ureidopropionic acid, hypoxanthine, inosine, and uric acid (nucleotide metabolism) were chosen as the biomarkers for evaluating the influence of dietary GA treatment on serum metabolites in puppies.4-nd urine –106. Thend urine . Consistl-valine, l-tyrosine, l-glutamic acid, phenylacetaldehyde, and tetrahydrodeoxycorticosterone were positively correlated with the relative abundance of Clostridium_sensu_stricto_1 (Firmicutes) and Escherichia–Shigella (Proteobacteria). However, interestingly, l-tyrosine and phenylacetaldehyde were oppositely correlated with and Lactobacillus (Lactobacillaceae). Serum l-lactic acid, alpha-linolenic acid, citric acid, oleic acid, and spermidine were positively correlated with Clostridium_sensu_stricto_1 and Escherichia–Shigella, whereas alpha-linolenic acid, oleic acid, and spermidine were negatively correlated with Lactobacillus (Lactobacillaceae). Simultaneously, the positive correlation between serum metabolites and bacteria were l-arginine , phytosphingosine and taurochenodeoxycholic acid (Eggerthellaceae), l-carnitine (Turicibacter), and dodecanoic acid and homovanillic acid (Eubacteriaceae); and serum arachidonic acid and glyceraldehyde had a positive association with Firmicutes and Turicibacter, respectively. Further research is needed to provide a clear explanation between GM and fecal and serum metabolome in puppies supplemented with GA.Spearman’s correlation analysis found that fecal The GA markedly reduced the incidence of diarrhea and alleviated multiple environmental stressor-induced oxidative stress and inflammatory responses in puppies. The microbiome and metabolomics analyses revealed that environmental stress caused intestinal microbiota and metabolic disorders, while GA reversed the abnormalities. The comprehensive microbiota and metabolite relationships were established. In summary, we systematically elucidated the beneficial effects of GA treatment on stressed dogs from the host-microbial metabolic axis point of view. Future studies that can focus on the interactions between microbiota and metabolites may prove efficacious for understanding the precise mechanisms of the beneficial effects of polyphenol on health.https://www.ncbi.nlm.nih.gov/bioproject/PRJNA782241.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 the Experimental Animal Ethics Committee of South China Agricultural University.KY generated the ideas, designed the study, detected the samples, and wrote the initial manuscript. LinZ and BD guided and revised the manuscript. XD and SJ participated in the data analysis and contributed to the draft of the manuscript. JD made feasible suggestions for the experimental design and manuscript. MZ analyzed the results. CW, ZQX, LimZ, AT, SY, PL, ZLX, SH, and FZ detected the samples. All authors contributed to the article and approved the submitted version.This project was supported by the National Natural Science Foundation of China (Grant Nos. 31790411 and 32002186), Natural Science Foundation of Guangdong Province (Grant No. 2020A1515010322), Guangdong Basic and Applied Basic Research Foundation (2019B1515210002), and Independent Research and Development Projects of Maoming Laboratory (2021ZZ003).AT is employed by Guangzhou Qingke Biotechnology Co., Ltd.The remaining 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Nigella sativa L. (Ranunculaceae), commonly referred to as black seeds or black cumin, is used in popular medicine  all over the world for the treatment and prevention of several diseases, including diabetes. This study aims to investigate the inhibitory effect of N. sativa extracts and fractions against the activities of intestinal α-glucosidase and pancreatic α-amylase in vitro, and to explain the inhibitory effect of these fractions against these enzymes by identifying their active compounds responsible for this effect and determine their modes of inhibition. To do so, N. sativa hexane and acetone extracts were prepared and analyzed by GC–MS and HPLC–DAD, respectively. The hexane extract was further fractioned into eight different fractions, while the acetone extract generated eleven fractions. The extracts as well as the resulting fractions were characterized and evaluated for their potential in vitro antidiabetic activity using intestinal α-glucosidase and pancreatic α-amylase inhibitory assays in vitro. Hexane extract and fractions were less active than acetone extract and fractions. In the case of intestinal α-glucosidase activity, the acetone fraction SA3 had a high inhibitory effect on intestinal α-glucosidase activity with 72.26 ± 1.42%, comparable to the effect of acarbose (70.90 ± 1.12%). For the pancreatic α-amylase enzymatic inhibitory assay, the acetone fractions showed an inhibitory capacity close to that for acarbose. In particular, the SA2 fraction had an inhibitory effect of 67.70 ± 0.58% and was rich in apigenin and gallic acid. From these fractions, apigenin, (−)-catechin, and gallic acid were further characterized for their inhibitory actions. IC50 and inhibition mode were determined by analyzing enzyme kinetic parameters and by molecular modeling. Interestingly, (−)-catechin showed a possible synergistic effect with acarbose toward α-glucosidase enzyme inhibition, whereas apigenin showed an additive effect with acarbose toward α-amylase enzymatic inhibition. Furthermore, we studied the toxicity of N. sativa hexane and acetone extracts as well as that of acetone fractions. The result of acute toxicity evaluation demonstrated that N. sativa extracts were nontoxic up to a concentration of 10 g/kg, except for fraction SA3. Taken together, these results indicate that N. sativa extracts and/or derived compounds could constitute promising nutraceuticals for the prevention and treatment of type 2 diabetes mellitus. Diabetes mellitus (DM) has been rising at an unprecedented rate around the world. DM is a severe, chronic, and multifaceted metabolic disease with serious repercussions, including long-term disruption, failure, and dysfunction of various vital organs ,2. The nIn diabetic patients, postprandial hyperglycemia is involved in the glycation of plasma and cellular proteins, which contributes to the development of diabetes complications. In this regard, the management of diabetes mellitus requires accurate postprandial glycemic control by decreasing glucose absorption. This is possible via the inhibition of carbohydrate enzymes .Intestinal α-glucosidase EC3.2.1.20) and pancreatic α-amylase (EC3.2.1.1) are essential enzymes for carbohydrate digestion and absorption and have been identified as effective therapeutic targets for modulating the pathologic postprandial hyperglycemia detected in T2DM patients [.20 and pClinically, drugs such as acarbose, voglibose, or miglitol are used for this purpose. However, these drugs often induce serious gastrointestinal side effects including stomach pain, flatulence, and diarrhea . As a reNigella sativa L.) is an annual herb from the Ranunculaceae family. Its black seeds have been used in traditional medicine for anticancer, analgesic, antidiabetic, anti-inflammatory, antihypertensive, antimicrobial, antioxidant, and immunomodulatory purposes [Black cumin -induced diabetes in rats resulted in a reduction in toxicology [N. sativa extract increased ACC phosphorylation, resulting in insulin sensitization [N. sativa extracts, but isolating active fractions or identifying active compounds from these extracts would allow for the attribution and rationalization of the antidiabetic behavior of N. sativa.Several studies have shown that operties ,19. N. s insulin ,19. In pxicology . In additization . The majN. sativa extracts and fractions against the activities of intestinal α-glucosidase and pancreatic α-amylase in vitro, and to explain the inhibitory effect of these fractions against these enzymes by identifying their active compounds responsible for this effect, determining their modes of inhibition, and evaluating their toxicity. The identification and characterization of the compounds were carried out by GC–MS and HPLC–DAD in comparison with local database abs standards. Inhibitory actions of potential antidiabetic compounds were further characterized by the determination of their IC50 values and inhibition modes both by analyzing enzyme kinetic parameters and by molecular modeling.That is why this study aims to investigate the inhibitory effect of All solvents and products of analytical grade (99.8%), silica gel, acarbose, apigenin, (−)-catechin, gallic acid, intestinal α-glucosidase, and pancreatic α-amylase were purchased from Sigma Aldrich .N. sativa seeds were purchased from a local organic market . The seeds were washed before being ground into a fine, homogeneous powder. This powder was then placed in the Soxhlet apparatus and extracted at 50 °C in general, simultaneously, using hexane and acetone  using high-purity grade silica gel column (pore size: 60 Å 63–200 µm) at ambient temperature and standard pressure. The solvent eluents of hexane and acetone extract separation were dichloromethane and cyclohexane with (2/8) and (5/5) Hexane and acetone extracts were analyzed by gas chromatography coupled to mass spectroscopy using Shimadzu  GCMS-QP2010. The column dimensions were  and the mobile phase used was helium gas. Ionization temperature was maintained at 200 °C during an analysis time of 28 min an electron ionization source with a single-quadrupole mass analyzer . Identification was possible by comparing fragments mass and retention time to standards through the computer library NIST147.LIB .v/v) (A) and acetonitrile, pH = 2.6 (B). The injection volume was 30 μL. The separation was done on gradient mode and the flow was maintained to 0.9 mL/min as previously described [Acetone extract and fractions were analyzed by HPLC using a Waters  e2695 HPLC system analysis with a C18 column that has  dimensions. Eluents were water/acetic acid  was first determined using serial dilution (data not shown), and then both this concentration and half of this concentration were used to evaluate for each in a vitro inhibition assay.N. sativa seed extracts and fractions against intestinal α-glucosidase activity was quantified colorimetrically by monitoring the glucose release from sucrose degradation, according to the protocol described by Ouassou et al. [N. sativa seed extracts or fractions solutions at two different concentrations (166 and 328 µg/mL) were added to the mixture. Then, tubes were incubated at 37 °C in a water bath for 25 min. The mixture was heated at 100 °C for 5 min to stop the enzymatic reaction, and the release of glucose was estimated by the glucose oxidase method using a commercially available auto-kit. The absorbance was measured at 500 nm, and the inhibition percentage was calculated using the below formula:The effect of the u et al. . The assControl 500 nm: Absorbance of enzymatic activity without inhibitor.ATest 500 nm: Absorbance of enzymatic activity in the presence of N. sativa extracts or fractions, or acarbose.AN. sativa seed extracts and fractions was studied according to the procedure described by Daoudi et al. [N. sativa extracts and fractions at two different concentrations (0.5 and 1 mg/mL) or acarbose . The mixtures were pre-incubated at 37 °C for 10 min. Then, 200 μL of starch (1% (w/v)) dissolved in phosphate buffer was added to each tube and were incubated for 20 min at 37 °C. To stop the enzymatic reaction 600 μL of DNSA color reagent was added. Hereafter, the tubes were incubated for 8 min at 100 °C, before being put in an ice-cold-water bath for a few minutes. The mixture was diluted by adding 1 mL of distilled water and the absorbance was measured at 540 nm. Inhibition percentage was calculated using the formula bellows:The inhibition of pancreatic α-amylase activity by i et al. . The assControl 540 nm: Absorption of enzymatic activity without inhibitor.ATest 540 nm: Absorption of enzymatic activity in the presence of N. sativa extracts or fractions, or acarbose.A50 value, various concentrations -catechin and gallic acid, and from 1 to 10 µM for acarbose) were used. The assays were conducted as described above. The concentration of each inhibitor causing the 50% activity inhibition was calculated from % activity vs inhibitor concentration curves using software ED50 plus v1.0 . The experiments were repeated three times. Fractional inhibitory concentrations (FICs) at the IC50 level were calculated for both potential inhibitors, as follows: FIC = IC50 drugs in combination with acarbose/IC50 potential inhibitor alone.To calculate the ICThe enzyme assay was conducted as described above using increasing concentrations of substrate  in presence of inhibitors -catechin and gallic acid for pancreatic α-amylase) used at 50 µM final concentration. Acarbose was used as a commercial drug at 5 µM. Lineweaver–Burk double reciprocal representation (plotting 1/velocity vs 1/substrate concentration) was used to assess inhibition mode, and kinetic parameters Km and Vmax were determined using the Michaelis-Menten equation.Secondary plots were used to establish the inhibition constants Ki .https://pubchem.ncbi.nlm.nih.gov/ (accessed on 25 March 2021)). Initial virtual screen with the whole enzyme was conducted with the following sizes of the grid box: 81 Å × 82 Å × 85 Å (for α-glucosidase) and 60 Å × 78 Å × 63 Å (for α-amylase) in the x, y, and z dimensions, respectively, to identify the most favorable binding site predicted by the program based on the lowest docking energy and maximum docking number. The docking was then refined using this site with a grid box of 25 Å (square).Docking data for the binding of apigenin and gallic acid with pancreatic α-amylase, (−)-catechin, and gallic acid with α-glucosidase were performed with PyRx virtual screening tool software, which includes Autodock 4 and Autodock Vina  and Pymol v2.1.1  to predict the conformation of these molecule ligands within the appropriate target binding site of pancreatic α-amylase (PDB: 2QMK) and α-glucosidase (PDB: 5NN5). The software Discovery Studio 2020  was used to determine the type of interaction and visualization in 2D, and UCSF Chimera 1.14  was used for the 3D representation of molecules and interaction residues. The docking protocol employed was described by Proença et al.  for α-glalbinos mice from the local animal husbandry department of the Faculty of Science, Mohammed First University . The animals were grouped in polycarbonate cages with soft bedding and ad libitum water and food access in an environmentally controlled room . All mice were cared for in compliance with the internationally accepted guide for the care and use of laboratory animals published by the U.S. National Institutes of Health [The present study was conducted by using Swiss f Health .n = 6; ♂/♀ = 1 each) for each plant extract and fraction. N. sativa extracts were administered orally at single doses of 1, 3, 5, 7, and 10 g/kg body weight, respectively, while the control group received 10 mL/kg of distilled water. N. sativa fractions were administered orally, at single doses of 0.1, 0.3, 0.5, and 0.7 g/kg of body weight. The signs of toxic effects and/or mortality were observed continuously after 2 h and every 24 h for 14 days after administration.Acute plant extracts’ toxicity was evaluated orally using albino mice (22–32 g). Thirty mice, after fasting for 16 h, were sorted into five groups . Multiple-group comparisons were analyzed by one-way analysis of variance (ANOVA). Statistical significance was accepted as Hexane and acetone are polar and lipophilic solvents, respectively, with major logP differences. Hexane is a nonpolar organic solvent with a high lipophilia (logP = +3.9), allowing it to extract only hydrophobic compounds. Acetone is a polar solvent with a logP = −0.16 that is closer to the lipophilic–hydrophilic boundary line than that of hydrophobic compounds, meaning that it can solubilize hydrophilic compounds much better than hydrophobic compounds. The aim of using these two solvents with such a large lipophilia difference is to isolate and separate compounds with very different physicochemical properties.N. sativa hexane extract (EH) was a brown liquid, whereas acetone extract (EA) had a thick caramel color and consistency. Yields calculated referring to N. sativa seeds weights. The highest yield was obtained with hexane (34.2% (w:w)), while a lower yield was obtained with acetone (2.0% (w/w)). Eight fractions (SH1–SH8) were obtained from EH, and eleven fractions (SA1–SA11) were obtained from EA. Except for fractions SA3, SA5, and SA11, the majority of fractions were yellow (SA11). The fraction SA3 was orange, the fraction SA5 was transparent, and the fraction SA11 was brownish.cis-9,12) and oleic (18:1 cis-9)), in higher amounts, and saturated ) acids is consistent with the composition of N. sativa [N. sativa oil that is used in the food industry or as an emollient in cosmetics [The presence of four major components from EH, predominantly fatty acids, was established using gas chromatography coupled to mass spectrometry (GC–MS) analysis: linoleic acid (64.52%), palmitic acid 30.33%), oleic acid (2.74%), and acetostearin (2.40%) . The occ. sativa ,32,33. A%, oleic osmetics .Considering their more hydrophilic nature, acetone extract (FA) and fractions (SA1-SA11) were characterized using high-performance liquid chromatography coupled to diode array detection (HPLC–DAD) .l-cysteine and l-histidine), and l-ascorbic acid. These compounds were partitioned into different fractions. Gallic acid was the most abundant component in fraction SA1, but it was also found in fractions SA2 and SA3. Apigenin was the main component of fraction SA2, which also included thymoquinone. Fraction SA3 was primarily composed of (−)-catechin, fraction SA4 of naringenin, and fraction SA7 of l-cysteine, with a trace of l-ascorbic acid. The last fraction with identified compounds, SA11, reassembled rutin, quercetin, and l-histidine. Fractions SA6 and SA8 were examples of fractions composed of four unidentified compounds, as were fractions SA9 and SA10 (data not shown). The phenolic content of N. sativa seeds was reported to be about 3% (w/w) of N. sativa seeds, which was in strong accordance with our acetone extraction yield [N. sativa seeds [N. sativa seeds.This analysis revealed the presence of thymoquinone, phenolic compounds -catechin) and gallic acid), amino acids , against intestinal α-glucosidase activity was determined .For mother extracts EH and EA, only a minor inhibition of intestinal α-glucosidase activity was observed . With the concentrations of extract or fraction added, the inhibition values generally rose, indicating the presence of at least one inhibitor of this enzyme in the considered extract/fraction. Acetone fractions showed a slightly higher inhibition compared to hexane fractions, with inhibition percentages ranging from 14.60 ± 1.12% (SH6) to 33.37 ± 0.31% (SH2) for hexane fractions and from 21.44 ± 1.54% (SA1) to 72.26 ± 1.42% (SA3) for acetone fractions. Polyphenolic compounds were more abundant in acetone fractions than in hexane fractions. The most active acetone fraction, SA3, was particularly rich in (−)-catechin and gallic acid. Several phenolics, including gallic acid and (−)-catechin, have been found to inhibit intestinal α-glucosidase, which supports this observation ,42,43,44Inhibitory capacity against pancreatic α-amylase was also determined for each extract and fraction at two doses (0.5 and 1.0 mg/mL) .The inhibition of acetone extract EA, 75.8 ± 0.36%) was greater than that of hexane extract  and very similar to that of the standard drug acarbose (at 5 µM). Only the fraction SH2 showed substantial inhibition 39.9 ± 6.7%) among the various hexane fractions examined, albeit at a lower level than the mother hexane extract (EH). This suggests that the inhibitory activity is certainly the result of synergy and that separating the hexane extract is not beneficial for pancreatic α-amylase inhibition. Acetone fractions, on the other hand, were significantly more active than hexane extracts, except for fractions SA3, SA6, and SA8, which were inactive against pancreatic α-amylase activity. The highest inhibition was obtained for fractions SA2 (67.70 ± 0.58%) and SA8 (67.22 ± 0.24%). According to HPLC–DAD analysis, fraction SA2 was rich in apigenin and gallic acid, while fraction SA8 had two unidentified compounds. The identification and characterization of these two compounds will be the focus of future studies. As with intestinal α-glucosidase, some experiments suggest that apigenin and gallic acid could be involved in this inhibition of pancreatic α-amylase [ ± 0.36% .9 ± 6.7%The evolution of the kinetic parameters of intestinal α-glucosidase in the presence of (−)-catechin, gallic acid, and thymoquinone (50 µM), and of pancreatic α-amylase in the presence of apigenin and gallic acid (50 µM), was investigated and compared to the action of acarbose (5 µM). These kinetic parameters were determined from Lineweaver–Burk plots .The results showed effective inhibition of intestinal α-glucosidase by both (−)-catechin and gallic acid, whereas thymoquinone was not active under the evaluated concentration range (data not shown). Similarly, both apigenin and gallic acid were effective inhibitors of pancreatic α-amylase. Contrary to acarbose, which acts as a competitive inhibitor (an increase of Km), Lineweaver–Burk plots indicated that (−)-catechin and gallic acid inhibit intestinal α-glucosidase in a noncompetitive manner by lowering its Vmax . The LinGiven that both enzymes are hydrolases with very similar catalytic mechanisms and substrate binding cavities, this result may appear surprising. It is worth noting that acarbose inhibits both enzymes using the same mechanism, which is understandable given that its structure resembles that of an oligosaccharide ,11. Howe50 values were calculated from IC50 plots -catechin or apigenin, could be used in combination with acarbose to treat T2DM without reducing the effectiveness of this drug.The IC50 plots , Table 2anage DM ,18,19. IThese results confirmed the binding of both compounds to intestinal α-glucosidase outside the active site, thus confirming their noncompetitive action. The calculated affinities were −7.2 kcal/mol and −6.0 kcal/mol for (−)-catechin and gallic acid, respectively, thus confirming our experimental enzymatic data. This difference in favor of (−)-catechin can be the consequence of more stable interactions as observed with an additional π-alkyl interaction (with R594 of the enzyme). Other conventional hydrogen bonds  and carbon–hydrogen bonds with E866 were observed for both (−)-catechin and gallic acid. Similarly, Zhang et al. [These results confirmed the binding of both compounds in the active site of the pancreatic α-amylase thus confirming their competitive action. The calculated affinities were −7.7 kcal/mol and −6.1 kcal/mol for apigenin and gallic acid, respectively, confirming our experimental enzymatic data. This difference in favor of apigenin can be the consequence of additional π–sigma interactions (with I235 and L162 of the enzyme) observed for apigenin in addition to π–π interaction  and conventional hydrogen bonds . Similar residues, interactions modes, and affinity values were identified for competitive binding of different polyphenols in the active site cavity of α-amylase ,12.N. sativa seed extracts and fractions was investigated  in vivo.The toxicity of stigated . The frastigated . These r effects . Other s effects ,50. Furt effects  and of N of rats  confirmeN. sativa seeds have traditionally been used for a variety of purposes, including potential antidiabetic properties. Moreover, some research on model animals has shown that it affects blood sugar. Diabetes mellitus management demands precise postprandial glycemic control, which can be achieved by inhibiting carbohydrate enzymes. As a result, it is conceivable that the effect of N. sativa seeds is related to an inhibitory effect on the digestive enzymes α-glucosidase and α-amylase.N. sativa seed extracts (hexane and acetone) as well as fractions of these extracts and evaluated their potential inhibitors on these two enzymes. The hexane (EH) and acetone (AE) extracts of N. sativa seeds, as well as their fractions (8 fractions (SH1–8) from EH and 11 fractions (SA1–11) from AE) obtained by column chromatography, were characterized by GC–MS and HPLC–DAD, resulting in the identification of 63 compounds (48 in hexane extract and 15 in acetone extract), which is the most comprehensive phytochemical characterization of N. sativa seeds to our knowledge.To test this hypothesis, we made different polarity N. sativa hexane and acetone extract and fraction against intestinal α-glucosidase and pancreatic α-amylase was then examined. The acetone fraction SA3 containing (−)-catechin and gallic acid inhibited intestinal α-glucosidase to the greatest extent. N. sativa extracts were also effective at inhibiting pancreatic α-amylase activity, with the acetone fraction SA2, which was rich in apigenin and gallic acid, being the most effective.The putative inhibitory activity of each N. sativa extracts and fractions were confirmed through additional characterization using several methodologies . All of these analyses pointed in the same direction, and while they support previous research, here, their inclusion in the same study allows for a more direct comparison of the data.The possible roles of apigenin, (−)-catechin, and gallic acid in the inhibitory activity of Considering the substantial gastrointestinal adverse effects of acarbose, the current promising therapeutic alternative is to explore natural inhibitors that can supplement or possibly replace this drug to reduce these side effects. Here, we demonstrated that (−)-catechin can act in synergy with acarbose to inhibit the α-glucosidase enzyme, whereas apigenin showed an additive effect with acarbose to inhibit the α-amylase enzyme. In that context, the current results are particularly significant.N. sativa extracts are nontoxic up to a concentration of 10 g/kg, allowing them to be evaluated further for future potential applications, in vivo.Finally, toxicity assay revealed that N. sativa seeds to treat DM, suggest a new inhibiting action on digestive enzymes that may support its hypoglycemic impact, and suggest that N. sativa extracts, fractions, and/or derived chemicals may be promising for the prevention and treatment of T2DM.Altogether our results support the traditional use of


Astragalus membranaceus in the treatment of sepsis.  The purpose of the present study was to explore the mechanism of Astragalus membranaceus using the TCMSP and BATMAN databases. Then, the GeneCards, MalaCards, and OMIM databases were used to screen out relevant targets of sepsis. The common targets of the former two gene sets were uploaded to the STRING database to create an interaction network. DAVID was used to perform KEGG enrichment analysis of the core targets. Based on the results of KEGG and previous studies, key pathways for the development of sepsis were identified and experimentally validated.  We searched the active components and targets of Astragalus membranaceus through data mining, corresponding to 1,130 targets. The intersection of the two types of targets led to a total of 318 common targets and 84 core targets were obtained after screening again. The KEGG and previous studies showed that these 84 core targets were involved in sepsis by regulating TNF, MAPK, and PI3K pathways. TNF, MAPK8, NF-κB, and IκBα are crucial in sepsis. Experimental validation demonstrated that some markers in sepsis model rats were improved after the intervention with Astragalus granules and their chemical components. Among them, IL-1β, IL-6, and TNF-α in rat serum were reduced. The mRNA and protein expression of TNF-α, IL-6, MMP9, MAPK8, and NF-κB were reduced in rat blood. However, the mRNA and protein expression of IκBα and PI3K were increased in rat blood.  We obtained 3,370 sepsis-related targets in databases and 59 active components in κBα and NF-κB, attenuate the expression of IL-6 and MMP9, and interfere with the inflammatory response during sepsis. The AST could affect the TNF, PI3K, and MAPK pathway cascade responses centred on I Sepsis is a systemic inflammatory disease caused by the overactivation of the immune system and a cascade of inflammatory molecules released in the body under stress conditions, such as infection by pathogenic microorganisms, trauma, or shock. Without timely and effective treatment, sepsis can develop into severe sepsis and threaten the patient's life , 2. EpidAstragalus membranaceus (AST) is a Chinese herb that is effective in treating sepsis. AST is the dry root of Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao. modern pharmacological studies have shown that AST and its constituents have good pharmacological effects on organ damage caused by sepsis. Astragaloside IV attenuates sepsis-induced intestinal barrier dysfunction by inhibiting RhoA/NLRP3 inflammasome signal transduction [Astragalus polysaccharides have a protective effect on septic heart dysfunction by inhibiting the TLR4/NF-κB signaling pathway [Astragalus saponins can also regulate the levels of serum myeloperoxidase, nitric oxide, and lactate dehydrogenase and reduce the mRNA expression of inducible nitric oxide synthase and interleukin-1β in the liver, alleviating sepsis caused by cecal ligation and puncture [sduction . Astraga pathway . Astragapuncture .Network pharmacology is a discipline that uses network visualisation and other technologies to reveal the complex biological network relationship among drugs, genes, diseases, and targets . Networkhttp://lsp.nwu.edu.cn/tcmsp.php) [http://bionet.ncpsb.org.cn/batman-tcm/). Based on the pharmacokinetic parameters of drug absorption, distribution, metabolism, and toxicity in the human body [P < 0.05 was used as the screening condition for chemical components in BATMAN database [The main chemical components of AST were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) (msp.php)  and Bioimsp.php)   ≥ 3man body  (DL) ≥ 0database . Accordihttps://www.omim.org/) and the Human Disease Database , and the Human Gene Database  were the searched target genes using “sepsis” as a keyword. After taking intersections of sepsis-related targets with AST targets, we obtained potential genes for AST in the treatment of sepsis.The Online Mendelian Inheritance in Man . Species was set as human; the minimum interaction threshold was set to “highest confidence” (>0.9) [The intersecting genes were imported into the STRING database 11.5 (” (>0.9) ; and the” (>0.9) .We imported the core genes and their corresponding components into Cytoscape 3.6.1 in order to construct the Drug-Target-Disease Network graph.P < 0.05 was set as statistically significant. Potential connections between pathways were also found by searching previous literature in PubMed, and the essential targets of the significant pathways were visualised using Cytoscape 3.6.1.To further understand the specific roles of the screened intersection networks in terms of gene function and related signaling pathways, KEGG pathway enrichment analysis was performed on the genes associated with the core targets using DAVID. A threshold of https://www.rcsb.org/) database, and compounds were obtained from the TCMSP database. The proteins and small molecules were optimised using SYBYL-X.2.0 software, and molecular docking was performed using the SurflexDock module. The interaction of the active ingredients with the target proteins was scored according to the total score scoring function, with larger total score values indicating better matching of the small molecule compound to the more significant protein. Generally, a score above 4.0 is considered to indicate some binding activity, and a value greater than 5.0 indicates that the molecule has strong binding to the target [Molecular docking was performed to validate the important targets screened by KEGG analysis as well as their more closely related chemically synthesised components. Protein targets were obtained from the RCSB PDB , Interleukin-6 (IL-6), Tumor Necrosis Factor (TNF-α) enzyme-linked immunoassay (ELISA) kits , LPS , rabbit polyclonal antibodies TNF-α, MAPK8, PI3K, IL-6 , GAPDH , rabbit monoclonal antibody IκBa, MMP9, NF-κB, and β Actin , Methanol , Astragalus granules were purchased from Baili Pharmaceutical Group in China (authorised document number: country medicine accurate character Z20003380), excipient , Interleukin-1We used the following instruments: HBS-1096A ELISA Analytical Instrument , adjustable micropipette , high-speed and low-temperature centrifuge , low-speed centrifuge , thermostat , 4°C refrigerators , 37°C incubation box , and QuantStudio 6 real-time quantitative PCR instrument ; High-Performance Liquid Chromatography  and PCR instrument .Astragalus granules in 10 mL of ultrapure water, add methanol to fix the volume to 50 mL, extract with ultrasound for 2 hours, and then place in a centrifuge at 4°C and centrifuge at 12000 rpm for 10 min. 1 mg standard product of cycloeucalenol is dissolved in 1 mL methanol. 1 mg standard product of encecalin is dissolved in 1 mL methanol. 1 mg standard product of kaempferol is dissolved in 1 mL methanol.Dissolve 4 g of ∗ 4.6 mm, 5 μm), the mobile phase is methanol, column temperature is 60°C, the flow rate is 1 mL/min, the drift tube temperature is 80°C, nebuliser temperature is 30°C, the nitrogen flow rate and gain is set to 25 psi and 100, respectively, and the injection volume is 10 μL.For the detection of cycloeucalenol, a Waters model 2695 HPLC with a Waters 2424 evaporative light detector was used. The chromatographic column is Diamonsil C18 (2) , the flow rate is 1 mL/min, the column temperature is 35°C, the detection wavelength is 254 nm, and the injection volume is 10 μL. The gradient elution process is shown in Encecalin was detected using a Waters Model 2695 HPLC with a DAD detector. The chromatographic column is Diamonsil C18 (2)  with a flow rate of 1 mL/min, a column temperature of 35°C, and a detection wavelength of 360 nm. The mobile phase was methanol : 0.1% phosphoric acid in water/50 : 50, and the injection volume was 10 μL.The instrument used for the determination of kaempferol was a Waters model 2695 HPLC with DAD detector. The chromatographic column was a Diamonsil C18 (2) .Seventy SD male rats aged 8∼9 weeks with bodyweight of (200 ± 30) g were used in this laboratory, all of which were provided by Changsha Tianqin Biotechnology Co. LTD.  2019-0014). According to the random number table method, they were randomly divided into 7 groups with 10 rats in each group, namely: control group, LPS group, LPS + Astragalus granule (0.8 g/kg), excipient (0.8 g/kg), cycloeucalenol (350 mg/kg), encecalin (14.1 mg/kg), and kaempferol (6.9 mg/kg), respectively, were administered by gavage for one week. LPS modelling was performed on all rats except control group 24 h after the last administration. In the control group, only normal saline was injected into the tail vein. Rats in other groups were injected with 10 mg/kg of LPS through tail vein according to body weight [After a week of adaptive feeding, each group of rats was given the appropriate intervention. y weight . Twenty-Behavior change, fur color, and mental state before and after modelling were observed. Death after modelling was recorded, and survival curves of rats in each group were drawn.β, IL-6, and TNF-α in serum were detected by ELISA kit. The operation was carried out in strict accordance with the instructions.After anaesthesia, abdominal aorta blood was taken and centrifuged. The supernatant was taken, and the contents of IL1-ΔΔCt value for IL-6, MAPK8, TNF-α, MMP9, PI3K, and NF-κB genes. β-actin was used as an internal reference gene to calculate the 2-ΔΔCt value for IκBα gene. The specific primers were as follows  according to the manufacturer's instructions, reverse transcribed into cDNA using the PrimeScript RT kit with genomic decontamination, and then amplified by PCR. GAPDH was used as an internal reference gene to calculate the 2μm size were immersed in primary antibody incubation solution and incubated overnight at 4°C. Antibody dilutions were as follows: GAPDH (1 : 1000), TNF (1 : 500), β-actin (1 : 200), MAPK8 (1 : 1000), PI3K (1 : 2000), NF-κB (1 : 1000), IL-6 (1 : 1000), IκBa (1 : 5000), and MMP9 (1 : 5000). Add the corresponding secondary antibody, soak the PVDF membrane in the secondary antibody incubation solution, and incubate for 2 h at 37°C in a shaker. Finally, the film was washed with TBST and developed with ECL luminescence. The films were scanned, and the results were analysed by ImageJ software for gel imaging systems.Use RIPA lysate to lyse the cells in the blood, use the BCA kit to determine the protein concentration, add the prepared protein sample to a 10% gel for electrophoresis, transfer the membrane, and then block it in 5% skim milk for 2 hours. PVDF membranes of 0.45 P < 0.05.All data were processed by SPSS 22.0 statistical software. The measured data are expressed as the mean ± standard deviation (mean ± SD). One-way ANOVA was used to compare multiple groups when the data were normally distributed and homogeneity of variance. Survival analysis was performed using the log-rank (Mantel–Cox) test function. Differences were indicated as statistically significant at After screening, the TCMSP database contains 8 compounds and 111 targets, and the BATMAN database contains 51 compounds and 1081 targets. After removing the blank and duplicate targets, a total of 59 chemical components and 1,130 drug targets were obtained , mainly including cancer, the TNF signaling pathway, Chagas disease, influenza A, hepatitis B, leishmaniasis, the MAPK signaling pathway, proteoglycans in cancer, osteoclast differentiation, Tollas disease, osteoclast differentiation, influenza A, hepatitis B, leishmaniasis, the MAPK signaling pathway, proteoglycans in cancer, osteoclast differentiation, the Toll-like receptor signaling pathway, toxoplasmosis, Salmonella infection, nonalcoholic fatty liver disease (NAFLD), the prolactin signaling pathway, measles, the chemokine signaling pathway, pertussis, the HIF-1 signaling pathway, neurotrophin signaling pathway, the PI3K-Akt signaling pathway, etc. In this study, the top 20 KEGG signaling pathways were screened according to the count value to generate a map , NF-κB1, and IκBα were the critical genes identified in κBα (PID: 6Y1J), NF-κB (PID: 1NFK), TNF (PID: 1DU3), and MAPK8 (PID: 4G1W) were selected from the RSCB PDB database for molecular docking. The main active components in AST enter the active site during the docking process with the core targets, indicating that the main active components and the core targets demonstrate good binding, which verifies the reliability of the results of this study. The total score results are shown in The main active components of AST obtained in (1) Determination of Substances and Prediction of LD50 Based on HPLC and Discovery Studio for Chemistry Components. In chromatographic analysis, samples of Astragalus granules showed the same retention times as the standard products of cycloeucalenol, encecalin, and kaempferol  General Situation and Survival Analyses. Compared with the control group, rats in the LPS group, LPS + Astragalus granules group, LPS + excipient group, LPS + cycloeucalenol group, LPS + encecalin group, and LPS + kaempferol group have decreased diet and water consumption. LPS group and LPS + excipient group have the worst mental state and weakened activities, while LPS + Astragalus granules group and LPS + cycloeucalenol group situation was significantly improved. When the time to death of the rats within 24 hours was counted, a significant difference was found in the survival curve of LPS group compared to control group (P < 0.01). This demonstrated that LPS has a strong lethal effect. The survival rate was significantly improved with the intervention of Astragalus granules and cycloeucalenol (P < 0.05)  Determination of the Serum IL-1β, IL-6, and TNF-α Levels in Rats by ELISA. IL-1β, IL-6, and TNF-α are critical inflammatory factors and biological markers of sepsis [β, IL-6, and TNF-α of serum expression of biological markers were increased in the LPS group compared to that in the control group (P < 0.01). The levels of IL-1β, IL-6, and TNF-α were downregulated after Astragalus granules intervention (P < 0.01). Cycloeucalenol significantly inhibited IL-1β (P < 0.01) and also suppressed the elevation of IL-6 and TNF-α to some extent (P < 0.05). Encecalin significantly inhibited TNF-α (P < 0.01) and also suppressed the elevation of IL-1β to some extent (P < 0.05). Kaempferol significantly inhibited IL-1β (P < 0.01) and also suppressed the elevation of IL-6 to some extent (P < 0.05) (as shown in f sepsis . They ca(4) Detection of TNF-α, IL-6, MMP9, MAPK8, PI3K, NF-κB, and IκBα mRNA Expression in Rat Blood by Real-Time qPCR. The result showed that the targets of TNF-α, IL-6, MMP9, MAPK8 (JNK), and NF-κB in the blood of rats in the LPS group were significantly higher than those in the blood of rats in the control group (P < 0.01), and PI3K and IκBα were substantially lower than those in the blood of rats in the control group (P < 0.01). This trend was reversed after Astragalus granules intervention (P < 0.01). In addition, cycloeucalenol, encecalin, and kaempferol also regulate the expression of these genes in the blood of the sepsis model to varying degrees. Among them, cycloeucalenol significantly inhibited the mRNA expression of MMP9 (P < 0.01) and the mRNA expression of inhibited MAPK8, TNF-α, and IL-6 (P < 0.05). Cycloeucalenol significantly upregulated PI3K expression (P < 0.01) and IκBα (P < 0.05). Encecalin inhibited the upregulation of MMP9, NF-κB, and TNF-α (P < 0.05). Encecalin upregulated PI3K expression (P < 0.05). Kaempferol inhibited the elevation of NF-κB and IL-6 (P < 0.05). These manifestations illustrate that Astragalus granules and their components can regulate the expression of these genes during transcription (as shown in (5) The Protein Expression Levels of TNF-α, IL-6, MMP9, MAPK8, PI3K, NF-κB, and IκBα in Rat Blood. Our study revealed significant changes in blood protein expression of core targets such as TNF-α, IL-6, MMP9, MAPK8, PI3K, NF-κB, and IκBα in LPS group after LPS intervention (P < 0.01). The protein expression of TNF-α, IL-6, MMP9, MAPK8, and NF-κB was significantly increased in the LPS group (P < 0.01), while the protein expression of PI3K and IκBα was significantly decreased (P < 0.01). These trends were significantly reversed in LPS + Astragalus granules group after intervention with Astragalus granules (P < 0.01). In addition, cycloeucalenol, encecalin, and kaempferol can also regulate the expression of related proteins in the blood of the sepsis model to varying degrees. Among them, cycloeucalenol significantly inhibited the expression of MMP9 (P < 0.01) and inhibited MAPK8, TNF-α, and IL-6 (P < 0.05). Cycloeucalenol significantly upregulated PI3K expression (P < 0.01) and IκBα (P < 0.05). Encecalin significantly inhibited the upregulation of MMP9 (P < 0.05), TNF-α, and NF-κB (P < 0.01). Encecalin significantly upregulated PI3K expression (P < 0.01). Kaempferol significantly inhibited NF-κB (P < 0.01) and IL-6 (P < 0.05) -dicentrine, 1-tetradecanol, cyperene, tetradecane, tridecene, elemicin, and other components can relieve the inflammatory response of the body. Stigmasterol can effectively inhibit the inflammatory response induced by LPS and has an excellent regulatory impact on the abnormal levels of serum liver enzyme markers, alanine aminotransferase, aspartate aminotransferase, ALT, and AST . Kaempfentestine . Cyperenntestine . Elemiciactivity . γ-sitosrophages . AST canκB1 were important in the progression of the disease. TNF is a bipolar molecule derived from macrophages and immune cells. When the body is activated during infection or tissue damage, it can transmit signals via ligands and receptors back to cells, causing subsequent inflammatory cascade reactions [α can not only induce a massive release of a variety of inflammatory factors and stimulate the development of inflammation [κB [κBα under the action of PI3k. IκBα can pass through the 300 amino acid residue Rel homology region. The Rel homology domain (RHD) interacts with IκBα to prevent the NF-κB dimer from entering the nucleus to exert its negative feedback regulation on NF-κB [κB pathways to aggravate the inflammatory response in the body.After analysing the PPI network, it was found that TNF, MAPK14, AKT1, MAPK8 (JNK), and NF-eactions . TNF-α cammation  but alsoammation  and stimammation . MAPK14 tion [κB . In thison NF-κB , 45. In κBα. Mitogen-activated protein kinase (MAPK) is an essential member of the intracellular signaling protein network that mediates extracellular stimuli to intracellular responses. The activation of its subtype JNK is based on thermal-induced apoptosis of macrophages, and the release of IL-6, MMP9, TNF-α, and other inflammatory factors further aggravates organ damage in patients with sepsis [α can effectively control the increase in MMP9 expression after initiation by MAPK8 (JNK) [α in combination with TNFR leads to the high expression of the transcription factor NF-κB and aggravates the inflammatory response throughout the body [κB dimer and IκBα in resting cells masks the nuclear localisation signal of NF-κB, but when stimulated, IκBα is degraded, so the NF-κB dimer is released into the nucleus and activates the transcription of target genes [κB is released, it initiates MAPK8 (JNK) and aggravates the inflammatory response [κBα [κB pathway. The TNF, MAPK, and PI3K signaling pathways are connected through IκBα and NF-κB. The interaction between these pathways in the pathogenesis of sepsis determines the degree of widespread inflammation throughout the body, and exchange among these three pathways may be achieved by affecting the balance of IκBα and NF-κB.According to the KEGG results and previous literature, we found that the PI3K signaling pathway, MAPK signaling pathway, and TNF signaling pathway played essential roles in the pathogenesis of sepsis. The PI3K (phosphatidylinositol-3-kinase) pathway is a crucial signaling pathway in the body, and it maintains tissue homeostasis by regulating protein phosphorylation, methylation, and ubiquitination . In sepsh sepsis . These ih sepsis . IL-6 ish sepsis , and it h sepsis . The proh sepsis . TNF-α cK8 (JNK) , and theK8 (JNK) . In addithe body . Under net genes . After Nresponse . The PI3nse [κBα , 60. Theγ-sitosterol, cycloeucalenol, kaempferol, encecalin, and cyperol bound well to the joint targets of TNF, MAPK8 (JNK), NF-κB, and IκBα in these three pathways. However, although we can determine the potential of binding between a compound and its target through this method, the biological changes of the target gene after binding are still unclear.Molecular docking technology is an essential means to confirm the interaction between a compound and its target . To veriAstragalus granules are not clear, the advantage of Chinese medicine lies in the superimposed effect of multiple features on multiple pathways. Core genes such as TNF-α, MAPK8 (JNK), NF-κB, and IκBα were validated by ELISA, real-time quantitative PCR, and western blot. The results showed that the levels of sepsis markers IL1β, IL-6, and TNFα in the blood of model rats and the mortality rate of rats were significantly increased after tail vein injection. These phenomena are closely related to alterations in the PI3K signaling pathway, MAPK signaling pathway, and TNF signaling pathway in rats. The high mortality of rats is often accompanied by an imbalance between their own internal NF-κB and IκBα.The balance between NF-κB and IκBα can be altered by the expression of key genes such as TNF-α, IL-6, MMP9, MAPK8, and PI3K. Fortunately, Astragalus granules and their components significantly modulated mortality and altered the expression of these key genes in rats.Because the interactions that occur among the chemical components of Astragalus granules. These compounds exhibit some targeting of the regulation of these key genes. For example, although cycloeucalenol has a modulating effect on most indicators, it has a weaker modulating effect on NF-κB. Encecalin can modulation of MMP9, TNF-α, PI3K, and NF-κB. Kaempferol is more likely to affect targets such as IL-6 and NF-κB. Therefore, to some extent, cycloeucalenol, encecalin, and kaempferol can all reduce the expression of inflammatory factors and reduce the mortality rate in rats.Indeed, the effects of cycloeucalenol, encecalin, and kaempferol are somewhat deviated compared to the effects of Astragalus granules may be the result of the combined action of its internal chemotactic components such as cycloeucalenol, encecalin, and kaempferol. The pharmacological effects of Astragalus granules cannot be replaced by their own internal chemotactic components. Of course, the results of this study are subject to the dose-effect relationship. In the future, we will further clarify the respective advantages of Astragalus granules and chemically combined ingredients to provide new ideas and approaches for clinical use.This demonstrates that the pharmacological action of κBα and NF-κB, attenuate the expression of IL-6 and MMP9, and interfere with the inflammatory response during sepsis.This study is based on network pharmacology and used the TCMSP, BATMAN, GeneCards, MalaCards, and OMIM databases to obtain AST and sepsis-related targets to identify shared genes between them. The AST could affect the TNF, PI3K, and MAPK pathway cascade responses centred on I