Identification of superior and rare haplotypes to optimize branch number in soybean.

KEY MESSAGE: Using the integrated approach in the present study, we identified eleven significant SNPs, seven stable QTLs and 20 candidate genes associated with branch number in soybean. Branch number is a key yield-related quantitative trait that directly affects the number of pods and seeds per soybean plant. In this study, an integrated approach with a genome-wide association study (GWAS) and haplotype and candidate gene analyses was used to determine the detailed genetic basis of branch number across a diverse set of soybean accessions. The GWAS revealed a total of eleven SNPs significantly associated with branch number across three environments using the five GWAS models. Based on the consistency of the SNP detection in multiple GWAS models and environments, seven genomic regions within the physical distance of ± 202.4 kb were delineated as stable QTLs. Of these QTLs, six QTLs were novel, viz., qBN7, qBN13, qBN16, qBN18, qBN19 and qBN20, whereas the remaining one, viz., qBN12, has been previously reported. Moreover, 11 haplotype blocks, viz., Hap4, Hap7, Hap12, Hap13A, Hap13B, Hap16, Hap17, Hap18, Hap19A, Hap19B and Hap20, were identified on nine different chromosomes. Haplotype allele number across the identified haplotype blocks varies from two to five, and different branch number phenotype is regulated by these alleles ranging from the lowest to highest through intermediate branching. Furthermore, 20 genes were identified underlying the genomic region of ± 202.4 kb of the identified SNPs as putative candidates; and six of them showed significant differential expression patterns among the soybean cultivars possessing contrasting branch number, which might be the potential candidates regulating branch number in soybean. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable branch numbers.

Genome-wide survey identified superior and rare haplotypes for plant height in the north-eastern soybean germplasm of China.

The proper and efficient utilization of natural genetic diversity can significantly impact crop improvements. Plant height is a quantitative trait governing the plant type as well as the yield and quality of soybean. Here, we used a combined approach including a genome-wide association study (GWAS) and haplotype and candidate gene analyses to explore the genetic basis of plant height in diverse natural soybean populations. For the GWAS analysis, we used the whole-genome resequencing data of 196 diverse soybean cultivars collected from different accumulated temperature zones of north-eastern China to detect the significant single-nucleotide polymorphisms (SNPs) associated with plant height across three environments (E1, E2, and E3). A total of 33 SNPs distributed on four chromosomes, viz., Chr.02, Chr.04, Chr.06, and Chr.19, were identified to be significantly associated with plant height across the three environments. Among them, 23 were consistently detected in two or more environments and the remaining 10 were identified in only one environment. Interestingly, all the significant SNPs detected on the respective chromosomes fell within the physical interval of linkage disequilibrium (LD) decay (± 38.9 kb). Hence, these genomic regions were considered to be four quantitative trait loci (QTLs), viz., qPH2, qPH4, qPH6, and qPH19, regulating plant height. Moreover, the genomic region flanking all significant SNPs on four chromosomes exhibited strong LD. These significant SNPs thus formed four haplotype blocks, viz., Hap-2, Hap-4, Hap-6, and Hap-19. The number of haplotype alleles underlying each block varied from four to six, and these alleles regulate the different phenotypes of plant height ranging from dwarf to extra-tall heights. Nine candidate genes were identified within the four haplotype blocks, and these genes were considered putative candidates regulating soybean plant height. Hence, these stable QTLs, superior haplotypes, and candidate genes (after proper validation) can be deployed for the development of soybean cultivars with desirable plant heights. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01363-7.

Exploration of a Brain-Liver-Communication-Related Mechanism Involved in the Experimental Perimenopausal Depression Rat Model using Chaihu-Shugan-San.

Existing research suggests the involvement of a brain-liver-communication-related mechanism in the occurrence of depression. In this study, we selected Chaihu-Shugan-San (CSS), a traditional Chinese herbal medicine that can simultaneously affect liver and depression, as a probe to investigate the involvement of the brain-liver-communication-related mechanism in perimenopausal depression. A total of 50 experimental perimenopausal depression rat models were established by ovariectomy surgery (PMS) followed by chronic unpredictable mild stress (CUMS) processes. Animals underwent CSS treatment or treatments with CSS + Ly294002, an inhibitor of the PI3K/Akt signalling pathway. We observed the behavioural performances of depression and anxiety, serum concentrations of biochemical indices, serum estrogen two levels, hippocampal 5-HT and NE levels and the morphological changes in liver tissues. The protein and mRNA expressions of PI3K and Akt were also evaluated. CSS treatment significantly ameliorated the behavioural performance, partial biochemical indices and the morphological changes in the liver tissues of PMS + CUMS rats. Ly294002 partially inhibited the CSS effects. The expressions of PI3K and Akt were significantly downregulated by PMS + CUMS processes but upregulated by CSS treatment, which could be significantly suppressed by Ly294002. A brain-liver-communication-related mechanism may be involved in perimenopausal depression, where the PI3K/Akt signalling pathway plays a vital role.

Fine mapping of a QTL locus (QNFSP07-1) and analysis of candidate genes for four-seeded pods in soybean.

Soybean [Glycine max (L.) Merr.] is an important grain and oil crop in the world, and it is the main source of high-quality protein. The number of four-seeded pods is a quantitative trait in soybean and is closely related to yield in terms of breeding. Therefore, it is of great significance to study the inheritance of four-seed pods and to excavate related genes for improving soybean yield. In this study, individuals with high ratio of four-seed pods which from chromosome segment substitution lines (CSSLs) that can be stably inherited were selected as the parent, and Suinong 14 (SN14) was used as recurrent parent to construct secondary mapping population via marker-assisted selection. From 2006 to 2017, QTL analysis was performed using secondary mapping populations, and the initial QTL mapping interval was 0.67 Mb and was located on Gm07. Based on the initial QTL mapping results, individuals that were heterozygous at the interval (36,116,118-37,399,738 bp) were screened in 2018, and the heterozygous individuals were subjected to inbreeding to obtain 13 F3 populations, with a target interval of 321 kb. Gene annotation was performed on the fine mapping interval, and 27 genes were obtained. Among 27 genes, Glyma.07G200900 and Glyma.07G201200 were identified as candidate genes. qRT-PCR was used to measure the expression of the 2 candidate genes at different developmental stages of soybean, and the expression levels of the 2 candidate genes in terms of cell division (axillary buds, COTs, EMs) were higher than those in terms of cell expansion (MM, LM), and these genes play a positive regulatory role in the formation of four-seeded pods. Haplotype analysis of 2 candidate genes which shows that Glyma.07G201200 has two excellent haplotypes, and the significance level between the two excellent haplotypes at p < 0.05. Those results provide the information for gene map-based cloning and molecular marker-assisted breeding of the number of four-seeded pod in soybean. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01265-6.

Fast Identification of Adverse Drug Reactions (ADRs) of Digestive and Nervous Systems of Organic Drugs by In Silico Models.

This study aimed to discover concurrences of adverse drug reactions (ADRs) and derive models of the most frequent items of ADRs based on the SIDER database, which included 1430 marketed drugs and 5868 ADRs. First, common ADRs of organic drugs were manually reclassified according to side effects in the human system and followed by an association rule analysis, which found ADRs of digestive and nervous systems often occurred at the same time with a good association rule. Then, three algorithms, linear discriminant analysis (LDA), support vector machine (SVM) and deep learning, were used to derive models of ADRs of digestive and nervous systems based on 497 organic monomer drugs and to identify key structural features in defining these ADRs. The statistical results indicated that these kinds of QSAR models were good tools for screening ADRs of digestive and nervous systems, which gave the ROC AUC values of 81.5%, 98.9%, 91.5%, 69.5%, 78.4% and 78.8%, respectively. Then, these models were applied to investigate ADRs of 1536 organic compounds with four phase and zero rule-of-five (RO5) violations from the ChEMBL database. Based on the consensus ADRs' predictions of models, 58.1% and 42.6% of compounds were predicted to cause these two ADRs, respectively, indicating the significance of initial assessment of ADRs in early drug discovery.

RNA Sequencing-Associated Study Identifies GmDRR1 as Positively Regulating the Establishment of Symbiosis in Soybean.

In soybean (Glycine max)-rhizobium interactions, the type III secretion system (T3SS) of rhizobium plays a key role in regulating host specificity. However, the lack of information on the role of T3SS in signaling networks limits our understanding of symbiosis. Here, we conducted an RNA sequencing analysis of three soybean chromosome segment substituted lines, one female parent and two derived lines with different chromosome-substituted segments of wild soybean and opposite nodulation patterns. By analyzing chromosome-linked differentially expressed genes in the substituted segments and quantitative trait loci (QTL)-assisted selection in the substituted-segment region, genes that may respond to type III effectors to mediate plant immunity-related signaling were identified. To narrow down the number of candidate genes, QTL assistant was used to identify the candidate region consistent with the substituted segments. Furthermore, one candidate gene, GmDRR1, was identified in the substituted segment. To investigate the role of GmDRR1 in symbiosis establishment, GmDRR1-overexpression and RNA interference soybean lines were constructed. The nodule number increased in the former compared with wild-type soybean. Additionally, the T3SS-regulated effectors appeared to interact with the GmDDR1 signaling pathway. This finding will allow the detection of T3SS-regulated effectors involved in legume-rhizobium interactions.

QTL analysis of nodule traits and the identification of loci interacting with the type III secretion system in soybean.

Symbiotic nitrogen fixation is the main source of nitrogen for soybean growth. Since the genotypes of rhizobia and soybean germplasms vary, the nitrogen-fixing ability of soybean after inoculation also varies. A few studies have reported that quantitative trait loci (QTLs) control biological nitrogen fixation traits, even soybean which is an important crop. The present study reported that the Sinorhizobium fredii HH103 gene rhcJ belongs to the tts (type III secretion) cluster and that the mutant HH103ΩrhcJ can clearly decrease the number of nodules in American soybeans. However, few QTLs of nodule traits have been identified. This study used a soybean (Glycine max (L.) Merr.) 'Charleston' × 'Dongnong 594' (C × D, n = 150) recombinant inbred line (RIL). Nodule traits were analysed in the RIL population after inoculation with S. fredii HH103 and the mutant HH103ΩrhcJ. Plants were grown in a greenhouse with a 16-h light cycle at 26 °C and an 8-h dark cycle at 18 °C. Then, 4 weeks after inoculation, plants were harvested for evaluation of nodule traits. Through QTL mapping, 16 QTLs were detected on 8 chromosomes. Quantitative PCR (qRT-PCR) and RNA-seq analysis determined that the genes Glyma.04g060600, Glyma.18g159800 and Glyma.13g252600 might interact with rhcJ.

Opioid Exposure is Associated with Aberrant DNA Methylation of OPRM1 Promoter Region in a Chinese Han Population.

The µ-opioid receptor (OPRM1) plays an important role in opiate addiction. The OPRM1 gene promoter showed hypermethylation in lymphocytes of opiate addicts as well as opioid medications users, while the methylation status displayed ethnic diversity. The purpose of the study was to investigate the methylation pattern of OPRM1 promoter in the Han Chinese population. We analyzed 22 CpG sites located in OPRM1 promoter in 186 former opiate addicts (94 males and 92 females) and 184 healthy controls (102 males and 82 females). The + 126 CpG site was significantly hypermethylated in the former heroin addicts compared with controls (13.67% versus 8.39%, [Formula: see text], corrected for 36 tests). Six CpG sites were significantly associated with opioid exposure, including the most significant +126 CpG site (opiate addicts 13.57%, control 8.39%, [Formula: see text], corrected for 36 tests), while the +23 GpG site was the only hypomethylated one in former opiate addicts compared with controls (P = 0.0023 after Bonferroni correction). Our results supported that opioid exposure was associated with methylation status of OPRM1 promoter and showed ethnic dependence.

Association between the traditional Chinese medicine pathological factors of opioid addiction and DRD2/ANKK1 TaqIA polymorphisms.

BACKGROUND: As we known, Traditional Chinese Medicine (TCM) helps to prevent the relapse of drug addiction. However, the scientific basis of TCM remains unclear because of limitations of current reductionist approaches. We aimed to explore the possible mechanism of how ANKK1 TaqIA (A1/A2) [rs1800497(T/C)] affects the relapse of opioid addiction on the perspective of Chinese traditional medicine. METHODS: The ANKK1 TaqIA (A1/A2) [rs1800497(T/C)] of the dopamine D2 receptor (DRD2) polymorphisms were genotyped in a case-control sample consisting of 347 opioid addicts and 155 healthy controls with RT-PCR and the TCM pathological factors were collected by means of Syndrome Elements Differentiation in the case-control sample. RESULTS: DRD2/ANKK1 TaqIA Polymorphisms has no relation with opioid addiction relapse; but for those who were diagnosed with phlegm syndrome, DRD2/ANKK1 TaqIA Polymorphisms affect the replapse of apioid addiction (P < 0.05). CONCLUSIONS: DRD2/ANKK1 TaqIA is associated with opioid addict and it is obvious in opioid addicts who suffer from the phlegm syndrome.

Effect of auricular pressing treatment on myopia in children.

OBJECTIVE: To observe the effect of pressing auricular points on myopia in children. METHODS: Myopic children aged 8-9 years were divided into two groups. The Chinese herb Semen Vaccariae was used to stimulate the auricular points of CO10, LO5, TF4, CO15, CO12, and CO13 for three treatment courses for the experimental group (n = 39), while the same therapy was not given to the control group (n = 33). Binocular naked vision of the experimental group and the control group before and after the intervention was measured using a standard E visual.acuity chart. RESULTS: There was no difference in the binocular naked vision between the experimental group and the control group before the intervention. In contrast, there was significant improvement in binocular naked vision in the experimental group after the intervention compared with the control group (P < 0.05). CONCLUSION: When combined with external medical application, non-invasive auricular therapy could improve the function of myopia in children. Auricular pressing was well received by the children.

The impact of vitamin D on the etiopathogenesis and the progression of type 1 and type 2 diabetes in children and adults.

Diabetes is a common chronic metabolic disease with complex causes and pathogenesis. As an immunomodulator, vitamin D has recently become a research hotspot in the occurrence and development of diabetes and its complications. Many studies have shown that vitamin D can reduce the occurrence of diabetes and delay the progression of diabetes complications, and vitamin D can reduce oxidative stress, inhibit iron apoptosis, promote Ca2+ influx, promote insulin secretion, and reduce insulin resistance. Therefore, the prevention and correction of vitamin D deficiency is very necessary for diabetic patients, but further research is needed to confirm what serum levels of vitamin D3 are maintained in the body. This article provides a brief review of the relationship between vitamin D and diabetes, including its acute and chronic complications.

In Silico Insights into Micro-Mechanism Understanding of Extracts of Taxus Chinensis Fruits Against Alzheimer's Disease.

BACKGROUND: The taxus chinensis fruit (TCF) shows promises in treatment of aging-related diseases such as Alzheimer's disease (AD). However, its related constituents and targets against AD have not been deciphered. OBJECTIVE: This study was to uncover constituents and targets of TCF extracts against AD. METHODS: An integrated approach including ultrasound extractions and constituent identification of TCF by UPLC-QE-MS/MS, target identification of constituents and AD by R data-mining from Pubchem, Drugbank and GEO databases, network construction, molecular docking and the ROC curve analysis was carried out. RESULTS: We identified 250 compounds in TCF extracts, and obtained 3,231 known constituent targets and 5,326 differential expression genes of AD, and 988 intersection genes. Through the network construction and KEGG pathway analysis, 19 chemicals, 31 targets, and 11 biological pathways were obtained as core compounds, targets and pathways of TCF extracts against AD. Among these constituents, luteolin, oleic acid, gallic acid, baicalein, naringenin, lovastatin and rutin had obvious anti-AD effect. Molecular docking results further confirmed above results. The ROC AUC values of about 87% of these core targets of TCF extracts was greater than 0.5 in the two GEO chips of AD, especially 10 targets with ROC AUC values greater than 0.7, such as BCL2, CASP7, NFKBIA, HMOX1, CDK2, LDLR, RELA, and CCL2, which mainly referred to neuron apoptosis, response to oxidative stress and inflammation, fibroblast proliferation, etc.Conclusions:The TCF extracts have diverse active compounds that can act on the diagnostic genes of AD, which deserve further in-depth study.

Estrogen restores disordered lipid metabolism in visceral fat of prediabetic mice.

BACKGROUND: Visceral obesity is increasingly prevalent among adolescents and young adults and is commonly recognized as a risk factor for type 2 diabetes. Estrogen [17ß-estradiol (E2)] is known to offer protection against obesity via diverse me-chanisms, while its specific effects on visceral adipose tissue (VAT) remain to be fully elucidated. AIM: To investigate the impact of E2 on the gene expression profile within VAT of a mouse model of prediabetes. METHODS: Metabolic parameters were collected, encompassing body weight, weights of visceral and subcutaneous adipose tissues (VAT and SAT), random blood glucose levels, glucose tolerance, insulin tolerance, and overall body composition. The gene expression profiles of VAT were quantified utilizing the Whole Mouse Genome Oligo Microarray and subsequently analyzed through Agilent Feature Extraction software. Functional and pathway analyses were conducted employing Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, respectively. RESULTS: Feeding a high-fat diet (HFD) moderately increased the weights of both VAT and SAT, but this increase was mitigated by the protective effect of endogenous E2. Conversely, ovariectomy (OVX) led to a significant increase in VAT weight and the VAT/SAT weight ratio, and this increase was also reversed with E2 treatment. Notably, OVX diminished the expression of genes involved in lipid metabolism compared to HFD feeding alone, signaling a widespread reduction in lipid metabolic activity, which was completely counteracted by E2 administration. This study provides a comprehensive insight into E2's local and direct protective effects against visceral adiposity in VAT at the gene level. CONCLUSION: In conclusion, the present study demonstrated that the HFD-induced over-nutritional challenge disrupted the gene expression profile of visceral fat, leading to a universally decreased lipid metabolic status in E2 deficient mice. E2 treatment effectively reversed this condition, shedding light on the mechanistic role and therapeutic potential of E2 in combating visceral obesity.

Causal relationship between gut microbiota and type 2 diabetes: a two-sample Mendelian randomization study.

Background: Studies showed that development of gut microbial dysbiosis has a close association with type 2 diabetes (T2D). It is not yet clear if there is a causal relationship between gut microbiota and T2D. Methods: The data collected from the published genome-wide association studies (GWASs) on gut microbiota and T2D were analyzed. Two-sample Mendelian randomization (MR) analyses were performed to identify causal relationship between bacterial taxa and T2D. Significant bacterial taxa were further analyzed. To confirm the findings' robustness, we performed sensitivity, heterogeneity, and pleiotropy analyses. A reverse MR analysis was also performed to check for potential reverse causation. Results: By combining the findings of all the MR steps, we identified six causal bacterial taxa, namely, Lachnoclostridium, Oscillospira, Roseburia, Ruminococcaceae UCG003, Ruminococcaceae UCG010 and Streptococcus. The risk of T2D might be positively associated with a high relative abundance of Lachnoclostridium, Roseburia and Streptococcus but negatively associated with Oscillospira, Ruminococcaceae UCG003 and Ruminococcaceae UCG010. The results of MR analyses revealed that there were causal relationships between the six different genera and T2D. And the reverse MR analysis did not reveal any evidence of a reverse causality. Conclusion: This study implied that Lachnoclostridium, Roseburia and Streptococcus might have anti-protective effect on T2D, whereas Oscillospira, Ruminococcaceae UCG003 and Ruminococcaceae UCG010 genera might have protective effect on T2D. Our study revealed that there was a causal relationship between specific gut microbiota genera and T2D.

Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes.

Subject: Major depressive disorder (MDD) negatively affects patients' behaviours and daily lives. Due to the high heterogeneity and complex pathological features of MDD, its diagnosis remains challenging. Evidence suggests that endoplasmic reticulum stress (ERS) is involved in the pathogenesis of MDD; however, relevant diagnostic markers have not been well studied. This study aimed to screen for ERS genes with potential diagnostic value in MDD. Methods: Gene expression data on MDD samples were downloaded from the GEO database, and ERS-related genes were obtained from the GeneCards and MSigDB databases. Differentially expressed genes (DEGs) in MDD patients and healthy subjects were identified and then integrated with ERS genes. ERS diagnostic model and nomogram were developed based on biomarkers screened using the LASSO method. The diagnostic performance of this model was evaluated. ERS-associated subtypes were identified. CIBERSORT and GSEA were used to explore the differences between the different subtypes. Finally, WGCNA was performed to identify hub genes related to the subtypes. Results: A diagnostic model was developed based on seven ERS genes: KCNE1, PDIA4, STAU1, TMED4, MGST1, RCN1, and SHC1. The validation analysis showed that this model had a good diagnostic performance. KCNE1 expression was positively correlated with M0 macrophages and negatively correlated with resting CD4+ memory T cells. Two subtypes (SubA and SubB) were identified, and these two subtypes showed different ER score. The SubB group showed higher immune infiltration than the SubA group. Finally, NCF4, NCF2, CSF3R, and FPR2 were identified as hub genes associated with ERS molecular subtypes. Conclusion: Our current study provides novel diagnostic biomarkers for MDD from an ERS perspective, and these findings further facilitate the use of precision medicine in MDD.

In Vitro Assessment of Cytochrome P450 2C19 Potential of Naoxintong.

The effects of Buchang Naoxintong Capsules (BNCs) on S-mephenytoin 4'-hydroxylation activities in human liver microsomes in vitro were assessed. Human liver microsome was prepared by different ultracentrifugation. Human liver microsome incubation experiment was carried out to assay BNC on S-mephenytoin 4'-hydroxylation activities. The 4'-hydroxylation of S-mephenytoin, a representative substrate toward CYP2C19, was increased by phenytoin sodium (positive control). After the incubation, the metabolites of the substrates (4'-OH-mephenytoin) were determined by HPLC. Results showed that both phenytoin sodium and BNC showed obvious increase effect on CYP2C19. The enzymatic reaction of BNC was observed with concentrations ranging from 5 µg/mL to 250 µg/mL. Compared to blank, the increase effect of BNC showed significant difference from the beginning of concentration of 150 µg/mL (P < 0.001). The conclusion was that BNC showed obvious increase effect on the catalytic activities of drug-metabolising CYP2C19 enzyme.

Exploring miRNA-related Molecular Targets of Erchen Decoction against Lipid Metabolism Disorder using a Network Pharmacologic Approach.

BACKGROUND: Erchen Decoction (ECD) is a complex herbal formulation widely used for treating lipid metabolism disorder (LMD) in China. This study aims to explore the microRNA (miRNA)-related molecular targets of ECD against LMD using a network pharmacology approach (NPA) Methods: We randomly divided 20 male Sprague Dawley rats into two groups; 10 rats were normal controls, and the other 10 rats were fed a high-fat diet (HFD) for 12 weeks to establish an LMD model. Differentially expressed miRNAs (DE-miRs, HFD vs. Control) in the rats' liver tissues were identified by miRNA sequencing and validated with qRT-PCR. Finally, the miRNArelated molecular targets for ECD activity against LMD were identified using a standard NPA by finding the intersection between identified DE-miRs-related targets and ECD-related targets. RESULT: We identified 8 DE-miRs and 968 targets and compared them to 262 ECD-related targets. A final list of 22 candidate targets was identified. Using a confidence score of >0.4, the network of (protein-protein interaction) PPI relationships exhibited 22 nodes and 67 edges. The GO and KEGG enrichment analyses revealed 171 molecular targets and 59 pathways, which were associated with ECD against LMD. CONCLUSION: The identified molecular targets and pathways suggest that complex mechanisms are involved in ECD's mechanism of action, and immune-inflammation-related mechanisms are closely associated with the effects of ECD. The targets obtained in this study will guide future studies on the pharmacologic effects of ECD.

TCM herbal prescription recommendation model based on multi-graph convolutional network.

ETHNOPHARMACOLOGICAL RELEVANCE: The recommendation of herbal prescriptions is a focus of research in traditional Chinese medicine (TCM). Artificial intelligence (AI) algorithms can generate prescriptions by analysing symptom data. Current models mainly focus on the binary relationships between a group of symptoms and a group of TCM herbs. A smaller number of existing models focus on the ternary relationships between TCM symptoms, syndrome-types and herbs. However, the process of TCM diagnosis (symptom analysis) and treatment (prescription) is, in essence, a "multi-ary" (n-ary) relationship. Present models fall short of considering the n-ary relationships between symptoms, state-elements, syndrome-types and herbs. Therefore, there is room for improvement in TCM herbal prescription recommendation models. PURPOSE: To portray the n-ary relationship, this study proposes a prescription recommendation model based on a multigraph convolutional network (MGCN). It introduces two essential components of the TCM diagnosis process: state-elements and syndrome-types. METHODS: The MGCN consists of two modules: a TCM feature-aggregation module and a herbal medicine prediction module. The TCM feature-aggregation module simulates the n-ary relationships between symptoms and prescriptions by constructing a symptom-'state element'-symptom graph (Se) and a symptom-'syndrome-type'-symptom graph (Ts). The herbal medicine prediction module inputs state-elements, syndrome-types and symptom data and uses a multilayer perceptron (MLP) to predict a corresponding herbal prescription. To verify the effectiveness of the proposed model, numerous quantitative and qualitative experiments were conducted on the Treatise on Febrile Diseases dataset. RESULTS: In the experiments, the MGCN outperformed three other algorithms used for comparison. In addition, the experimental data shows that, of these three algorithms, the SVM performed best. The MGCN was 4.51%, 6.45% and 5.31% higher in Precision@5, Recall@5 and F1-score@5, respectively, than the SVM. We set the K-value to 5 and conducted two qualitative experiments. In the first case, all five herbs in the label were correctly predicted by the MGCN. In the second case, four of the five herbs were correctly predicted. CONCLUSIONS: Compared with existing AI algorithms, the MGCN significantly improved the accuracy of TCM herbal prescription recommendations. In addition, the MGCN provides a more accurate TCM prescription herbal recommendation scheme, giving it great practical application value.

Construction of Chromosome Segment Substitution Lines and Inheritance of Seed-Pod Characteristics in Wild Soybean.

Genetic populations provide the basis for genetic and genomic research, and chromosome segment substitution lines (CSSLs) are a powerful tool for the fine mapping of quantitative traits, new gene mining, and marker-assisted breeding. In this study, 213 CSSLs were obtained by self-crossing, backcrossing, and marker-assisted selection between cultivated soybean (Glycine max [L.] Merr.) variety Suinong14 (SN14) and wild soybean (Glycine soja Sieb. et Zucc.) ZYD00006. The genomes of these 213 CSSLs were resequenced and 580,524 single-nucleotide polymorphism markers were obtained, which were divided into 3,780 bin markers. The seed-pod-related traits were analyzed by quantitative trait locus (QTL) mapping using CSSLs. A total of 170 QTLs were detected, and 32 QTLs were detected stably for more than 2 years. Through epistasis analysis, 955 pairs of epistasis QTLs related to seed-pod traits were obtained. Furthermore, the hundred-seed weight QTL was finely mapped to the region of 64.4 Kb on chromosome 12, and Glyma.12G088900 was identified as a candidate gene. Taken together, a set of wild soybean CSSLs was constructed and upgraded by a resequencing technique. The seed-pod-related traits were studied by bin markers, and a candidate gene for the hundred-seed weight was finely mapped. Our results have revealed the CSSLs can be an effective tool for QTL mapping, epistatic effect analysis, and gene cloning.

Role of Parameter Setting in Electroacupuncture: Current Scenario and Future Prospects.

Acupuncture is an ancient therapeutic method based on the theory of Chinese medicine (CM). Traditional acupuncture has many limitations; it is subjective and relies more on the experience of an acupuncturist, and the efficacy is sometimes irreproducible. In contrast, electroacupuncture (EA) has special characteristics in terms of objectivity and stability, thereby gaining considerable attention. Parameter setting plays a crucial role in EA practice. The current paper summarizes the current situation and limitations of parameter setting in EA practice. Objectification is the tendency and future of CM as well as EA. With the development of computerized technologies, such as wearable sensors, vast data, and artificial intelligence, CM syndromes can be successfully objectified. We propose the development of a novel self-feedback-adjust EA system, which may improve the parameter setting in EA and be beneficial to both the patients and clinicians.