Comparative efficacy and safety of Chinese patent medicines of iron deficiency anemia during pregnancy:A network meta-analysis

BACKGROUND Iron deficiency anemia(IDA)is a prevalent nutritional disorder during pregnancy.Clinical studies indicate that incorporating Chinese patent medicines(CPMs)with oral iron(OI)in treating IDA in pregnancy can reduce adverse effects and improve clinical outcomes.Nonetheless,the comparative efficacy of different CPMs remains unclear.AIM To assess the safety and effectiveness of different CPMs for treating IDA during pregnancy using network meta-analysis.METHODS We conducted a search for randomized controlled trials(RCTs)that combined CPM and OI for IDA treatment in pregnancy,spanning from 2013 to the present.Data analysis was performed using Rev Man 5.3 and Stata 14.0 on literature that satisfied the quality criteria.RESULTS The analysis included 45 RCTs,encompassing 4422 pregnant patients with IDA.Six CPMs were examined,including Shengxuebao Mixture,Shengxuening Tablets(SXN),Yiqi Weixue CPMs(YQWX),Jianpi Shengxue CPMs(JPSX),Yiqi Buxue Tablets,and Compound Hongyi Buxue Oral Liquid(FFHY).Findings indicated that FFHY+OI significantly improved the clinical effective rate.SXN+OI was most effective in boosting red blood cells counts and hemoglobin levels.YQWX+OI showed superior results in improving serum ferritin,and SXN+OI was most effective in increasing serum iron levels.JPSX+OI was optimal in reducing adverse pregnancy outcomes,while YQBX+OI effectively minimized adverse events.A cluster analysis suggested that SXN+OI could be the potentially optimal therapeutic regimen for IDA in pregnancy.CONCLUSION This study demonstrates that the combination of OI with CPMs offers better outcomes than OI alone.Based on clinical efficacy and other measured outcomes,SXN+OI emerges as the most effective treatment modality for improving the health of pregnant patients with IDA.

Ecological Networks of Allometric Growth,Feeding Behavior and Gut Microbiota in Chinese Alligator Hatchlings

Chinese alligator hatchlings in captivity are fragile and have a high mortality rate within first year.The body mass gain of reptile animals is closely related to their feeding behavior and gut microbiota.This study analyzed the intrinsic factors influencing the allometric growth of Chinese alligator hatchlings based on their body mass gain,feeding behavior,and gut microbiota.This information would enhance the health management of Chinese alligator hatchlings.There was a significant correlation between the total distance moved,the average number of conspecifics nearby,and body mass gain.Chinese alligator hatchlings with a greater growth rate showed greater activity and more independent behavior during feeding than those with a lower growth rate.Moreover,after feeding started,some functions of the gut microbiota showed significant relationships with growth rate and feeding activity.Chinese alligator hatchlings with a greater growth rate showed greater levels of heme biosynthesis than those with a lower growth rate,and feeding activity was inhibited by long-chain fatty acid biosynthesis.These results elucidate the relationships between health,feeding behavior,and the gut microbiota of Chinese alligator hatchlings.Understanding the intrinsic factors of their health and feeding behavior can improve the health management of Chinese alligator hatchlings in captivity for conservation.

A U-Shaped Network-Based Grid Tagging Model for Chinese Named Entity Recognition

Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.

Effectiveness and safety of traditional Chinese medicine decoction for diabetic gastroparesis:A network meta-analysis

BACKGROUND Diabetic gastroparesis(DGP)is a prevalent complication of diabetes that impairs people's quality of life and places a significant financial burden on them.The gastrointestinal symptoms of DGP patients can be improved by several Traditional Chinese Medicine(TCM)decoctions that have been shown to be effective in treating the disease.There are still many unanswered questions regarding the identification of appropriate therapeutic agents for the treatment of DGP in clinical practice.AIM To analyze the efficacy of several TCM decoctions in the treatment of DGP using Bayesian network meta-analysis for reference.METHODS PubMed,EMBASE,Cochrane Library,Web of Science,China National Knowledge Infrastructure,The China Biology Medicine DVD,Wanfang,and CQVIP were searched from inception to September 17,2022,to collect randomized controlled trials(RCTs)about TCM decoctions for DGP.Clinical effects and symptom scores were the primary outcomes.Additionally,we assessed motilin(MOT),somatostatin(SS),gastrin(GAS),gastric emptying rate,gastric emptying time,and adverse drug events as secondary outcomes.RESULTS A total of 67 eligible RCTs involving 4790 DGP patients and 7 TCM decoctions were included.The results of network meta-analysis(NMA)and surface under the cumulative ranking curve showed that with western medicine(WM)as a common control,the Banxia Xiexin Decoction(BXXD)+WM was most effective in clinical effects and enhancing early satiety scores;the Simo decoction(SMD)+WM was most effective in improving nausea and vomiting scores and anorexia scores,bloating scores;the Chaishao Liujunzi Decoction(CSLJD)was most effective in MOT,the Zhishi Xiaopi Decoction(ZSXPD)was most effective in SS and upgrading emptying rate;the Jianpi Xiaozhi Decoction was most effective in GAS;the CSLJD+WM was most effective in improving gastric emptying time.CONCLUSION These NMA results suggest that the BXXD+WM and SMD+WM may be one of the potential optimal treatments.Due to various limitations,further large-sample,double-blind,multi-center randomized RCTs are needed.

Effectiveness and safety of traditional Chinese medicine for diabetic retinopathy:A systematic review and network meta-analysis of randomized clinical trials

BACKGROUND Diabetic retinopathy(DR)is currently recognized as one of the most serious diabetic microangiopathies and a major cause of adult blindness.Commonly used clinical approaches include etiological control,microvascular improvement,and surgical intervention,but they are ineffective and have many side effects.Oral Chinese medicine(OCM)has been used for thousands of years to treat DR and is still widely used today,but it is unclear which OCM is more effective for DR.AIM To estimate relative effectiveness and safety profiles for different classes of OCMs for DR,and provide rankings of the available OCMs.METHODS The search time frame was from the creation of the database to January 2023.RevMan 5.3 and Stata 14.0 software were used to perform the systematic review and Network meta-analyses(NMA).RESULTS A total of 107 studies and 9710 patients were included,including 4767 cases in the test group and 4973 cases in the control group.Based on previous studies and clinical reports,and combined with the recommendations of Chinese guidelines for the prevention and treatment of DR,9 OCMs were finally included in this study,namely Compound Xueshuantong Capsules,Qiming Granules,Compound Danshen Dripping Pills,Hexue Mingmu Tablets(HXMM),Qiju Dihuang Pills(QJDH),Shuangdan Mingmu Capsules(SDMM),Danggui Buxue Decoction(DGBX),Xuefu Zhuyu Decoction and Buyang Huanwu Decoction.When these nine OCMs were analyzed in combination with conventional western medicine treatment(CT)compared with CT alone,the NMA results showed that HXMM+CT has better intervention effect on the overall efficacy of DR patients,HXMM+CT has better effect on improving patients'visual acuity,SDMM+CT has better effect on inhibiting vascular endothelial growth factor,DGBX+CT has better effect on reducing fundus hemorrhage area,HXMM+CT has better effect on reducing fasting blood glucose,and QJDH+CT has better effect on reducing glycated hemoglobin.When there are not enough clinical indicators for reference,SDMM+CT or HXMM+CT treatments can be chosen because they are effective for more indicators and demonstrate multidimensional efficacy.CONCLUSION This study provides evidence that combining OCMs with CT leads to better outcomes in all aspects of DR compared to using CT alone.Based on the findings,we highly recommend the use of SDMM or HXMM for the treatment of DR.These two OCMs have demonstrated outstanding efficacy across multiple indicators.

Comparative efficacy of traditional Chinese herbal injection for chronic renal failure:A systematic review and network meta-analysis of randomized controlled trials

Objective: To conduct a systematic review and network meta-analysis(NMA) for the comparison of the efficacy and safety of Chinese herbal injection(CHI) combined with Western medicine(WM) and WM monotherapy for chronic renal failure(CRF).Methods: Eight databases were searched from inception to August 30, 2022. Randomized controlled trials(RCTs) regarding the comparison of CHI-WM combination therapy and WM monotherapy were included. Literature search, risk-of-bias assessment, and data extraction were conducted by 2 reviewers independently. NMA was performed by Stata 14.0, R 4.0.4 software, and the latest risk of bias assessment tool 2(RoB 2).Results: A total of 53 RCTs were finally included, involving 4445 participants and 16 CHIs. RoB 2 showed that 2 of these studies had a high risk of bias. Tianqi injection(TQ) + WM was the most effective in reducing serum creatinine(Scr) level. Xingding injection(XD) + WM was the most effective in reducing blood urea nitrogen(BUN) and cystatin C(Cys C) levels. Guhong injection(GH) + WM had the highest endogenous creatinine clearance rate(Ccr). Shuxuetong injection(SXT) + WM was the most effective in improving the clinical effective rate. Danhong injection(DH) + WM resulted in the lowest 24-h urinary protein quantity(24 h-UPQ), while Danshen injection(DS) + WM led to the lowest blood uric acid(UA)level. Shenfu injection(SF) + WM was the most effective in increasing hemoglobin(Hb) level.Conclusion: CHIs-WM combination therapy is more effective than WM monotherapy in treating CRF.Considering all of the indicators, SK + WM may be the optimal treatment option for improving renal function in patients with CRF.

Synergistic effects of carbon cycle metabolism and photosynthesis in Chinese cabbage under salt stress

Chinese cabbage(Brassica rapa ssp. pekinensis) has a long cultivation history and is one of the vegetable crops with the largest cultivation area in China. However, salt stress severely damages photosynthesis and hormone metabolism, nutritional balances, and results in ion toxicity in plants. To better understand the mechanisms of salt-induced growth inhibition in Chinese cabbage, RNA-seq and physiological index determination were conducted to explore the impacts of salt stress on carbon cycle metabolism and photosynthesis in Chinese cabbage. Here, we found that the number of thylakoids and grana lamellae and the content of starch granules and chlorophyll in the leaves of Chinese cabbage under salt stress showed a time-dependent response, first increasing and then decreasing. Chinese cabbage increased the transcript levels of genes related to the photosynthetic apparatus and carbon metabolism under salt stress, probably in an attempt to alleviate damage to the photosynthetic system and enhance CO_(2) fixation and energy metabolism. The transcription of genes related to starch and sucrose synthesis and degradation were also enhanced;this might have been an attempt to maintain intracellular osmotic pressure by increasing soluble sugar concentrations. Soluble sugars could also be used as potential reactive oxygen species(ROS) scavengers, in concert with peroxidase(POD)enzymes, to eliminate ROS that accumulate during metabolic processes. Our study characterizes the synergistic response network of carbon metabolism and photosynthesis under salt stress.

Syntax-Based Aspect Sentiment Quad Prediction by Dual Modules Neural Network for Chinese Comments

Aspect-Based Sentiment Analysis(ABSA)is one of the essential research in the field of Natural Language Processing(NLP),of which Aspect Sentiment Quad Prediction(ASQP)is a novel and complete subtask.ASQP aims to accurately recognize the sentiment quad in the target sentence,which includes the aspect term,the aspect category,the corresponding opinion term,and the sentiment polarity of opinion.Nevertheless,existing approaches lack knowledge of the sentence’s syntax,so despite recent innovations in ASQP,it is poor for complex cyber comment processing.Also,most research has focused on processing English text,and ASQP for Chinese text is almost non-existent.Chinese usage is more casual than English,and individual characters contain more information.We propose a novel syntactically enhanced neural network framework inspired by syntax knowledge enhancement strategies in other NLP studies.In this framework,part of speech(POS)and dependency trees are input to the model as auxiliary information to strengthen its cognition of Chinese text structure.Besides,we design a relation extraction module,which provides a bridge for the overall extraction of the framework.A comparison of the designed experiments reveals that our proposed strategy outperforms the previous studies on the key metric F1.Further experiments demonstrate that the auxiliary information added to the framework improves the final performance in different ways.

Understandings of Urban Sustainability in China:a Bibliometric Analysis Using Chinese Literatures

Cities hold a critical responsibility for achieving the Sustainable Development Goals(SDGs)due to their high population density,extensive resource consumption,and significant economic contributions.To examine the present state of understandings regarding urban sustainability(SDG 11:Sustainable Cities and Communities)within Chinese research communities,this study collected 15950 papers from 1994 to 2022 on the 12 indicators of SDG 11,from the China National Knowledge Infrastructure(CNKI),a hub of Chinese academic papers,that directly relate to policymaking.Significant research topics on SDG 11 were identified for each indicator using bibliometrics analysis approaches.The high-frequency keywords and clusters of keywords over the last three decades reveal that existing studies primarily concentrated on the physical aspects,such as transportation and environment,while there is a lack of consideration of societal aspects.This indicates a limited and biased understanding of the urban sustainability within the Chinese academic community.Hence,it is crucial to prioritize the societal aspects in order to develop a research agenda that further advances urban sustainability.

Online Peer Advice: Giving Advice on Chinese Social Networking Sites

This study investigates advice-giving in peer-to-peer comment sections on Chinese social networking sites. The results show that advice, explanation, experience, and assessment are the four most frequent discursive moves in Chinese advice given by peers on social networking sites. Involvement, mitigation, and face-threatening strategies are also utilized frequently by those peers to give directives and express empathy and solidarity on Chinese online sites, thereby building supportive relationships among them in online communities. The online peer advice-giving in this study is influenced by multiple aspects of the platform, participants, and language use, presenting distinctive characteristics that differ from other studies.

Effectiveness and safety of seven oral Chinese patent medicines as adjuvant therapy for cancer-related anemia: A systematic review and network meta-analysis of randomized controlled trials

Objective:To evaluate the effectiveness and safety of seven oral Chinese patent medicines(CPMs)as adjuvant therapy for cancer-related anemia(CRA)by network meta-analysis(NMA).Methods:A literature search to obtain randomized controlled trials(RCTs)of seven oral CPMs in the adjuvant treatment of CRA was conducted in multiple databases from the inception to April 2022.The RevMan5.3 and R 4.1.1 software were used for NMA.Results:We ultimately included 29 RCTs with 2140 patients.Traditional meta-analysis showed that Fufang E'jiao syrup(FFEJS),Shengxuebao mixture(SXBM),Shengxuening tablets(SXNT),Jianpi Shengxue granules(JPSXG),and Yixuesheng capsule(YXSC)combined with basic Western treatment(BWT)could improve the hemoglobin(HGB)level.JPSXG combined with BWT could improve the red blood cell(RBC).FFEJS combined with BWT improved the Karnofsky performance status(KPS).NMA showed that FFEJS,JPSXG,SXBM,and SXNT plus BWT improved HGB better than Shengxue tablets(SXT)plus BWT,with top three ranking results being JPSXG plus BWT>SXNT plus BWT>FFEJS plus BWT.FFEJS plus BWT,JPSXG plus BWT,SXBM plus BWT,SXNT plus BWT,and SXT plus BWT improved RBC better than BWT,with top three ranking results being SXNT plus BWT>JPSXG plus BWT>FFEJS plus BWT.In terms of the KPS score,compared with SXT plus BWT,FFEJS,JPSXG,SXBM,SXNT,and Yizhong Shengxue capsule(YZSXC)plus BWT had higher KPS,with top three ranking results being SXBM plus BWT>JPSXG plus BWT>FFEJS plus BWT.Conclusions:Our NMA demonstrated that seven oral CPMs used as adjuvant treatment of CRA had a definite clinical effect.JPSXG not only increases the levels of HGB and RBC to enhance the clinical effect but also improves patients'quality of life.More accurate conclusions need to be verified by more high-quality RCTs.

A deep-learning-based approach for seismic surface-wave dispersion inversion(SfNet)with application to the Chinese mainland

Surface-wave tomography is an important and widely used method for imaging the crust and upper mantle velocity structure of the Earth.In this study,we proposed a deep learning(DL)method based on convolutional neural network(CNN),named SfNet,to derive the vS model from the Rayleigh wave phase and group velocity dispersion curves.Training a network model usually requires large amount of training datasets,which is labor-intensive and expensive to acquire.Here we relied on synthetics generated automatically from various spline-based vS models instead of directly using the existing vS models of an area to build the training dataset,which enhances the generalization of the DL method.In addition,we used a random sampling strategy of the dispersion periods in the training dataset,which alleviates the problem that the real data used must be sampled strictly according to the periods of training dataset.Tests using synthetic data demonstrate that the proposed method is much faster,and the results for the vS model are more accurate and robust than those of conventional methods.We applied our method to a dataset for the Chinese mainland and obtained a new reference velocity model of the Chinese continent(ChinaVs-DL1.0),which has smaller dispersion misfits than those from the traditional method.The high accuracy and efficiency of our DL approach makes it an important method for vS model inversions from large amounts of surface-wave dispersion data.

Topic-Aware Abstractive Summarization Based on Heterogeneous Graph Attention Networks for Chinese Complaint Reports

Automatic text summarization(ATS)plays a significant role in Natural Language Processing(NLP).Abstractive summarization produces summaries by identifying and compressing the most important information in a document.However,there are only relatively several comprehensively evaluated abstractive summarization models that work well for specific types of reports due to their unstructured and oral language text characteristics.In particular,Chinese complaint reports,generated by urban complainers and collected by government employees,describe existing resident problems in daily life.Meanwhile,the reflected problems are required to respond speedily.Therefore,automatic summarization tasks for these reports have been developed.However,similar to traditional summarization models,the generated summaries still exist problems of informativeness and conciseness.To address these issues and generate suitably informative and less redundant summaries,a topic-based abstractive summarization method is proposed to obtain global and local features.Additionally,a heterogeneous graph of the original document is constructed using word-level and topic-level features.Experiments and analyses on public review datasets(Yelp and Amazon)and our constructed dataset(Chinese complaint reports)show that the proposed framework effectively improves the performance of the abstractive summarization model for Chinese complaint reports.

Discussion on Scaffolding Teaching Mode of Traditional Chinese Medicine under the Background of Internet

This study was conducted to explore the construction of scaffolding teaching mode of Traditional Chinese Medicine under the background of"Internet+".The students of Grade 2018 majoring in traditional Chinese medicine were selected as the object,and some chapters of the textbook of traditional Chinese medicine were selected and taught by the traditional teaching mode while interspersing the scaffolding teaching mode,in order to help the implementation of the scaffolding teaching model.We adopted the methods of setting up situational scaffolding,question scaffolding and guide scaffolding to carry out relevant teaching contents.The scaffolding instruction model has a good degree of participation,and to a certain extent,it stimulates students'self-consciousness and enthusiasm,and improves their ability of analyzing and solving problems and their spirit of innovation.

Network Meta-analysis of nerve block combined with Chinese medicine for lumbar disc herniation

Objective:To evaluate the clinical efficacy of Chinese medicine methods(acupuncture,tui na,acupuncture knife,traditional Chinese medicine,traction)combined with nerve block treatment for lumbar disc herniation using Bayesian mesh Meta-analysis.Methods:Randomized controlled studies of TCM methods combined with nerve block for lumbar disc herniation in CNKI,Wanfang,Vip,China Biomedical Literature Library,Pubmed,Web of science,and The Cochrance Library databases were searched for the period from the establishment of each database to May 2021.2 researchers independently followed the developed nerf criteria to Screening was performed.Bayesian model mesh Meta-analysis was performed using R,RStudio,and addis-1.16.6 software.Results:Twenty-seven papers with a total of 2074 subjects were finally included,involving six interventions,namely nerve block alone,herbal medicine combined with nerve block,acupuncture combined with nerve block,acupuncture combined with nerve block,traction combined with nerve block,and tui na combined with nerve block.The results of the net analysis showed that(1)in terms of efficiency,all interventions were better than simple nerve block except for traction combined nerve block,and acupuncture,acupuncture,tui-na and Chinese medicine combined nerve block were better than traction combined nerve block respectively,and the probability ranked first for acupuncture combined nerve block.(2)On the VAS score,except for traction combined with nerve block,other interventions were superior to simple nerve block,and the combination of herbal medicine,acupuncture,and acupuncture respectively was superior to traction combined with nerve block,and the intervention with the best probability ranking result was herbal medicine combined with nerve block.(3)There was no statistical difference between the two interventions compared in terms of JOA scores,and the probability ranked first for herbal medicine combined nerve block.Conclusion:Chinese medicine combined nerve block was superior to nerve block alone,and Chinese medicine combined nerve block and acupuncture combined nerve block measures were more effective in the treatment of LDH,and traction combined nerve block was less effective.

Methodological survey of using Bayesian Network for predicting pharmacology-based bioactivities of Chinese medicines:a scoping review

Background:It seems to be numerous unclear black-box mechanisms of Chinese Medicines(CMs)with multiple bioactivities in the real-world clinical practice.Meanwhile,prior prediction is necessary before the implementation of pharmacodynamics-pharmacokinetics-based researches.With emergent ML techniques for TCM domain,Bayesian Network(BN)has shown its potentials for CM-bioactivity prediction and syndromes identification in Traditional Chinese Medicine(TCM),benefited from many advantages,such as flexibility in addressing,data-driven and probability-based inference under complex uncertainty.Although BN has been extensively used in TCM,the scarcity of researches on refining methodological features of BN-modelling for optimization poses a significant challenge.Our goal is to present methodological overview of BN-modelling for CM-bioactivities prediction towards pharmacology,which tends to acquire a sequence of intimations for boosting in-depth and optimized CM-BN collaboration based on detected gaps.Methods:We performed systematic search of 13 databases from their inception to November 10th 2022 regardless of language written,which excluded unindexed journals and clinical trial registries,using the 3 keywords(CM,Pharmacology,BN).And full-text original researches with the given subject were under consideration.Afterwards,selection of eligible studies,data refinement and inspection were totally conducted by 6 review authors.Results:A total of 7 studies involving 17 BN models were included for synthesis and refinement,based on existing literatures and databases with 2 modelling functions:regression and tagging.There were 3 prediction patterns:property-bioactivity,efficacy-bioactivity and constituent-bioactivity inference,covering 8 feature-utilized efficacies,5 feature-utilized properties and 10 feature-utilized constituents.Thereafter,without an independent validation dataset,established BNs were mostly utilized to predict the root-node probabilities of unknown data.Indeed,incomplete report on modelling samples,directed acyclic graphs,conditional probability tables and algorithms hindered us from gathering information.Conclusion:A spot of studies were found in this work.And current evidence suggested that some breakthroughs should be achieved in CM-BN integration in the future.At last,to our knowledge,we preliminarily proposed certain recommendations and elicited implications for future work.

Discovering the efficacy and mechanism of Chinese herbal medicine for distal symmetric polyneuropathy via integrating meta-analysis and network pharmacology analysis

Objective Chinese herbal medicine(CHM)has been commonly used in Distal Symmetric Polyneuropathy(DSPN)treatment with satisfactory clinical effects,but the underlying pharmacological mechanism of CHM on DSPN remains unclear.We aimed to identify frequently used clinically effective CHM and its potential pharmacological mechanisms for DSPN by conducting meta-analysis and network pharmacology analysis.Methods We searched both Chinese and English databases from March 1990 to October 2022.Studies that met the inclusion criteria were selected for meta-analysis.After extracting the relevant data,we performed meta-analysis and frequency analysis.The active compounds and predicted targets of high-frequency herbs and DSPN-related targets were extracted from public databases.Then we conducted network construction,Gene Ontology(GO)enrichment,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis to discover the potential pharmacological mechanisms.Results Sixteen articles were selected for meta-analysis,and nine high-frequency CHMs were identified,including Radix Astragali seu Hedysari,Rhizoma Ligustici,Caulis Spatholobi,Radix Salviae Miltiorrhizae,Radix Paeoniae Alba,Flos Carthami,Radix Notoginseng,Radix Rehmanniae Recens,Rhizoma Corydalis.Fourteen hub targets including STAT3,CTNNB1,MAPK14,SRC,AKT1,TP53,EGFR,JUN,RELA,MAPK1,FOS,CCND1,HSP90AA1,MYC,and ten active compounds including Quercetin,Kaempferol,Luteolin,Apigenin,beta-sitosterol,Stigmasterol,Caffeic Acid,Aeginetic Acid,Vanillin,and Lauric Acid were identified by network analysis.Enrichment analysis showed that the biological process of hub targets included transcriptional regulation,cell proliferation,redox processes,apoptosis processes,ERK1 and ERK2 cascades,hypoxia reactions,MAPK cascades,and inflammatory responses.The main signalling pathways included HIF,TNF,and PI3K-AKT pathways.Conclusion Nine herbs were involved in the clinical therapeutic effect of CHM on DSPN treatment,and they may exert an anti-DSPN effect by regulating cell proliferation,apoptosis,and redox processes.

Network pharmacology and data analysis method to explore the traditional Chinese medicine regulates ferroptosis key genes in the occurrence and prognosis of lupus nephritis

Purpose:To explore the traditional Chinese medicine(TCM)regulates ferroptosis key genes in the occurrence and development of lupus nephritis(LN)based on biological information database.Patients and methods:Ferroptosis related genes were identified based on FerrDb database and literature retrieval.Used the OMIM,Gene Cards,Drug Bank to obtain the targets of LN.Cytoscapes 3.8.2 software and STRING database were used to analyze protein-protein interaction(PPI)network.Metacape software and Weishengxin were used to analyze the gene ontology(GO)classification and Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis.UniProt Database and Traditional Chinese Systems Pharmacology Database and Analysis Platform analysis platform were used to obtain the data table of key TCM and related targets.Cytoscapes 3.8.2 software was used to analyze the PPI network.Results:A total of 401 ferroptosis-related genes,361 LN related genes and 21“Ferroptosis-LN”intersection genes were obtained.Ferroptosis in the occurrence and prognosis of LN mainly involved the inflammatory response,cell activation,positive regulation of chemokine production and it was mainly involved in necroptosis,inflammatory bowel disease,ferroptosis and other pathways.A total of 412 TCMs containing key genes of“Ferroptosis-LN”were acquired.The most key genes were contained in Mahuang,Gehua,Baiguo,Chuanniuxi,Jinyinhua.15 key genes of“TCM-LN”were obtained.5 ferroptosis-related key genes in LN regulated by TCM were obtained,which were IL1β,TLR4,IFNG,STAT3 and HMOX1.Conclusion:TCM,such as Mahuang,Gehua,Baiguo,Chuanniuxi,Jinyinhua,may affect the occurrence and development of LN through the key ferroptosis genes,such as IL1B,TLR4,IFNG,STAT3 and HMOX1.

Topology and Semantic Information Fusion Classification Network Based on Hyperspectral Images of Chinese Herbs

Most methods for classifying hyperspectral data only consider the local spatial relation-ship among samples,ignoring the important non-local topological relationship.However,the non-local topological relationship is better at representing the structure of hyperspectral data.This paper proposes a deep learning model called Topology and semantic information fusion classification network(TSFnet)that incorporates a topology structure and semantic information transmis-sion network to accurately classify traditional Chinese medicine in hyperspectral images.TSFnet uses a convolutional neural network(CNN)to extract features and a graph convolution network(GCN)to capture potential topological relationships among different types of Chinese herbal medicines.The results show that TSFnet outperforms other state-of-the-art deep learning classification algorithms in two different scenarios of herbal medicine datasets.Additionally,the proposed TSFnet model is lightweight and can be easily deployed for mobile herbal medicine classification.

Effect of Modified Biochar with Organic Fertiliser on the Growth and Development of Chinese Rose

In order to reduce the waste of resources and environmental pollution caused by excessive application of chemical fertilizers, improve the utilization rate of fertilizers, and promote the large-scale and high-quality development of the Chinese rose industry. In this experiment, corn stover biochar, phosphoric acid modified biochar and organic fertilizer were used as test materials, and the effects of mixed application of modified biochar and organic fertilizer on the growth and development of Chinese rose as well as soil physicochemical properties were investigated by using the method of pot planting test. The results showed that modified biochar with organic fertilizer had the most significant effect on the enhancement of soil pH, organic matter content and soil carbon-to-nitrogen ratio. After 120 d of planting, modified biochar with organic fertilizer had the most significant effect on the enhancement of plant height and crown width of Chinese rose;both organic fertilizer and modified biochar with organic fertilizer significantly increased the chlorophyll content of Chinese rose. The number of flowers and the number of branches were the highest in the modified biochar with organic fertilizer treatment. In conclusion, the application of modified biochar with organic fertilizer can better improve the soil pH, and increase the soil organic matter content and carbon-to-nitrogen ratio to change the biological traits of Chinese rose. The results of this study provide a theoretical basis for the reduction of chemical fertilizers and the resource utilization of agricultural wastes and guarantee the sustainable development of the cut flower industry.