Predicting bioactive compounds and cancer-related molecular targets of lotus seedpod (Receptaculum Nelumbinis) based on network pharmacology and molecular docking

Background:Lotus seedpod(Receptaculum Nelumbinis)is the abundant by-products produced during lotus seed processing,and the sources are usually considered to be wastes and are abandoned outdoors or incinerated.This study aims at predicting its bioactive compounds and cancer-related molecular targets against six cancers,including lung cancer,gastric cancer,liver cancer,breast cancer,ovarian cancer and cervical cancer.Methods:Network pharmacology and molecular docking methods were performed.Results:Network pharmacology results indicated that 14 core compounds(liensinine,tetrandrine,lysicamine,tricin,sanleng acid,cireneol G,ricinoleic acid,linolenic acid,5,7-dihydroxycoumarin,apigenin,luteolin,morin,quercetin and isorhamnetin)and 10 core targets(AKT1,ESR1,HSP90AA1,JUN,MAPK1,MAPK3,PIK3CA,PIK3R1,SRC and STAT3)were screened for lotus seedpod against the six cancers.Molecular docking analysis suggested that the binding abilities between the core compounds and the core targets were mostly strong.GO analysis revealed that the intersected targets between the bioactive compounds of lotus seedpod and the six cancers were significantly related to biological processes,cell compositions and molecular functions.KEGG analysis showed that PI3K-Akt,TNF,Ras,MAPK,HIF-1 and C-type lectin receptor signaling pathways were notably involved in the anti-cancer activities of lotus seedpod against the six cancers.Conclusions:14 core compounds and 10 core targets were screened for lotus seedpod against lung cancer,gastric cancer,liver cancer,breast cancer,ovarian cancer and cervical cancer.This study supports the application of lotus seedpod in treating cancers,and promotes the recycling and the high-value utilization.

Lightweight detection method for lotus seedpod in natural environment

In order to solve the problems of the current target detection algorithms,such as poor discrimination of occluded targets,multiple parameters,complex networks,large amounts of computation,and not conducive to the deployment of mobile terminals,a lightweight lotus seedpod detection method based on YOLOv5s model was proposed in this study.First,the dataset was augmented by using a combination of offline and online augmentation,which improved the adaptability and robustness of the model in complex environments.Then,a lightweight Ghost convolution module was introduced to replace the original convolution,and a lightweight bidirectional feature pyramid network was designed,which could enhance the feature extraction and fusion capability of the network and reduce the amount of calculation and model size;On this basis,the combination of WIoU loss function and Mish activation function was adopted to improve the accuracy of feature extraction.Finally,the knowledge distillation training strategy was used to ensure the proposed lightweight model has the learning ability of a complex network model,improving the recall and precision of model detection.The results of the ablation study show that the proposed method effectively improves the detection performance of the YOLOv5s model for lotus seedpods.The mean average precision of the improved model was 89.7%,compared with the original YOLOv5s model increased by 2.8%,and the parameters and FLOPs were reduced by 2.36M and 7.3G,respectively.Compared with other detection algorithm models,the proposed algorithm model has the advantages of less computation,smaller model size,and higher detection precision.Therefore,the proposed improved optimization method based on the YOLOv5s model can effectively detect lotus seedpods,which provides theoretical research and technical support for intelligent picking of lotus seedpods in the actual operating environment.

Adsorption of 17β-estradiol from aqueous solution by raw and direct/pre/post-KOH treated lotus seedpod biochar

Five biochars derived from lotus seedpod(LSP)were applied to examine and compare the adsorption capacity of 17β-estradiol(E2)from aqueous solution.The effect of KOH activation and the order of activation steps on material properties were discussed.The effect of contact time,initial concentration,p H,ionic strength and humic acid on E2 adsorption were investigated in a batch adsorption process.Experimental results demonstrated that the pseudo second-order model fitted the experimental data best and that adsorption equilibrium was reached within 20 hr.The efficiency of E2 removal increased with increasing E2 concentration and decreased with the increase of ionic strength.E2 adsorption on LSP-derived biochar(BCs)was influenced little by humic acid,and slightly affected by the solution p H when its value ranged from 4.0 to 9.0,but considerably affected at p H 10.0.Low environmental temperature is favorable for E2 adsorption.Chemisorption,π–πinteractions,monolayer adsorption and electrostatic interaction are the possible adsorption mechanisms.Comparative studies indicated that KOH activation and the order of activation steps had significant impacts on the material.Post-treated biochar exhibited better adsorption capacity for E2 than direct treated,pretreated,and raw LSP biochar.Pyrolyzed biochar at higher temperature improved E2 removal.The excellent performance of BCs in removing E2 suggested that BCs have potential in E2 treatment and that the biochar directly treated by KOH would be a good choice for the treatment of E2 in aqueous solution,with its advantages of good efficiency and simple technology.