Search Results (132)

In this study, the design and synthesis of a novel series of cinnamic acid and 1,2,4-triazole hybrids were reported, aiming to enhance antioxidant and lipoxygenase inhibitory activities through pharmacophore combination. Cinnamic acid derivatives and 1,2,4-triazoles exhibit a broad spectrum of biological activities; therefore, by synthesizing hybrid molecules, we would like to exploit the beneficial characteristics of each scaffold. The general synthetic procedure comprises three synthetic steps, starting from the reaction of appropriate substituted cinnamic acid with hydrazine monohydrate in acetonitrile with cyclohexane and resulting in the formation of hydrazides. Consequently, the hydrazides reacted with phenylisothiocyanate under microwave irradiation conditions. Then, cyclization proceeded to the 1,2,4-triazole after the addition of NaOH solution and microwave irradiation. All the synthesized derivatives have been studied for their ability (a) to interact with the free radical DPPH, (b) inhibit lipid peroxidation induced by AAPH, and (c) inhibit soybean lipoxygenase. The synthesized derivatives have shown significant antioxidant activity and have been proved to be very good lipoxygenase inhibitors. Compounds 4b and 4g (IC₅₀ = 4.5 μM) are the most potent within the series followed by compound 6a (IC₅₀ = 5.0 μM). All the synthesized derivatives have been subjected to docking studies related to soybean lipoxygenase. Compound 4g exhibited a docking score of −9.2 kcal/mol and formed hydrophobic interactions with Val126, Tyr525, Lys526, Arg533, and Trp772, as well as a π−cation interaction with Lys526. Full article

In order to mitigate the reduction in soybean yield caused by soil salinization, a soybean gene, GmSNF4, which promotes plant tolerance to salt–alkali stress, was identified in this study. The STRING database was used to predict the interaction between GmSNF4 and GmPKS4. The GmPKS4 gene was experimentally shown to be involved in salt–alkali stress tolerance. Firstly, the yeast two-hybrid technique and bimolecular fluorescence complementation (BiFC) technique were used to confirm the interaction between GmSNF4 and GmPKS4: the AMPK-CBM-CBS1 conserved domain was thereby determined to be the region of the GmSNF4 protein involved in the interaction. Secondly, the GmSNF4 gene was induced by salt–alkali stress according to qRT-PCR analysis, and the GmSNF4 protein was localized in the nucleus and cytoplasm. Finally, analysis of GmSNF4’s role in resistance to salt–alkali stress in transgenic soybean plants showed that transgenic lines had better phenotypic, physiological, and stress-related gene expression than non-transgenic soybeans. Thus, GmSNF4 may play a significant role in plant salt–alkali stress tolerance. Full article

Soybeans are a primary source of plant-based protein, with seeds containing approximately 40% protein—a key quality trait. Selecting superior hybrid combinations and managing progeny effectively are crucial for developing high-protein soybean varieties. Using a recombinant inbred line population (RIL3613) derived from Dongnong L13 × Heihe 36 and its previously constructed high-density genetic linkage map, QTLs and QTL × environment interactions (QEIs) associated with seed protein content (SPC) were identified through the bi-parental population (BIP) model and multi-environment trials (MET) model in QTL IciMapping v4.2. Candidate genes were then predicted via sequence alignment and haplotype analysis between the parents. Finally, simulated breeding was conducted using the B4L function in the In Silico Breeding (ISB) module of the Blib platform to determine optimal breeding strategies across diverse environments. The analysis identified 19 QTLs associated with SPC and 97 QEIs linked to SPC. These QTLs collectively explained 84.442% of the phenotypic variance, with four QTLs exhibiting significant contributions. A key candidate gene, Glyma.12G231400, associated with soybean SPC, was predicted within the 38,995,090–39,293,825 bp interval on chromosome 12. Across 11 environments, three to six optimal breeding schemes were selected, all employing modified pedigree selection. These findings enhance our understanding of the genetic basis of soybean protein formation and provide technological support for molecular breeding for seed quality improvement. Full article

Soybean, an important leguminous crop valued for its high protein and oil content, obtains most of its nitrogen through symbiotic fixation processes. The symbiosis between soybeans and rhizobium can provide sufficient nitrogen for soybean growth. However, the signaling pathways underlying the establishment of the symbiosis are not so clear, especially the rhizobial type III effector-induced host response. In this study, we found that the single mutant HH103 nopAA::kan significantly affected the nodule number in soybeans. To further demonstrate the NopAA-triggered response in soybeans. Initial quantitative real-time PCR (qRT-PCR) tests showed that NopAA affects the expression of the soybean gene GmERF5, which was significantly upregulated upon inoculation with HH103 nopAA::kan, acting as a positive regulator of nodulation. The direct interaction between NopAA and GmERF5 was confirmed through yeast-two hybrid analysis. Furthermore, overexpression of GmERF5 in hairy roots indicated that GmERF5 may underlie the nodule phenotype of soybeans in response to NopAA. These findings provide new insights into the mechanisms by which soybean genes respond to rhizobial type III effectors to regulate symbiosis. Full article

Free radicals and inflammation have pivotal role in various degenerative diseases like cancer, rheumatoid arthritis, diabetes, cardiovascular and neurodegenerative disorders. Pyrazoles possess a wide range of biological activities such as antifungal, antituberculosis, antimicrobial, antiviral, anti-inflammatory, anti-convulsant, anticancer etc. In this present study a series of dibenzalacetones and the corresponding pyrazole hybrids were designed through bioisosterism, synthesized and biologically evaluated to highlight the importance of the extended conjugated system and substitution to the anti-inflammatory and antioxidant activity. The synthesis of dibenzalacetones was achieved via Claisen-Schmidt reaction. The dihydro-pyrazoles were synthesized from the substituted dibenzacetones and phenylhydrazines, hydrazine and semicarbazide under microwave irradiation optimizing reaction conditions. The synthesized compounds were spectroscopically characterized and evaluated for their anti-lipid peroxidation (AAPH) activity, their interaction with the free radical DPPH and the inhibition of soybean LOX. The novel derivatives were studied in terms of their physicochemical properties. Many of the dihydro-pyrazoles showed potent antioxidant properties and significant inhibition of soybean lipoxygenase as a result of their physicochemical features. Compounds 4a and 4b presented the most potent anti-lipid peroxidation abilities (98% and 97%), whereas compounds 2d and 2e have proved to be the most potent lipoxygenase inhibitors with IC₅₀ values 2.5 μM and 0.35 μM. Moreover, docking studies with soybean lipoxygenase highlight the interactions of the novel derivatives with the enzyme. Full article

With the expansion of global trade, China’s commodity futures market has become increasingly intertwined with regional maritime logistics. The Ningbo Containerized Freight Index (NCFI), as a key regional indicator, reflects freight rate fluctuations and logistics efficiency in real time. However, limited research has explored how commodity futures data can enhance NCFI forecasting accuracy. This study aims to bridge that gap by proposing a hybrid deep learning model that combines recurrent neural networks (RNNs) and gated recurrent units (GRUs) to predict NCFI trends. A comprehensive dataset comprising 28,830 daily observations from March 2017 to August 2022 is constructed, incorporating the futures prices of key commodities (e.g., rebar, copper, gold, and soybeans) and market indices, alongside Clarksons containership earnings. The data undergo standardized preprocessing, feature selection via Pearson correlation analysis, and temporal partitioning into training (80%) and testing (20%) sets. The model is evaluated using multiple metrics—mean absolute Error (MAE), mean squared error (MSE), root mean square error (RMSE), and R²—on both sets. The results show that the RNN–GRU model outperforms standalone RNN and GRU architectures, achieving an R² of 0.9518 on the test set with low MAE and RMSE values. These findings confirm that integrating cross-market financial indicators with deep sequential modeling enhances the interpretability and accuracy of regional freight forecasting. This study contributes to sustainable shipping strategies and provides decision-making tools for logistics firms, port operators, and policymakers seeking to improve resilience and data-driven planning in maritime transport. Full article

To solve the missed and wrong detection problems of the object detection model in identifying soybean companion weeds, this paper proposes an enhanced multi-scale channel feature model based on RT-DETR (EMCF-RTDETR). First, we designed a lightweight hybrid-channel feature extraction backbone network, which consists of a CGF-Block module and a FasterNet-Block module working together, aiming to reduce the amount of computation and the number of parameters while improving the efficiency of feature extraction. Second, we constructed the EA-AIFI module. This module enhances the extraction of detailed features by combining the in-scale feature interaction module with the Efficient Additive attention mechanism. In addition, we designed an Enhanced Multiscale Feature Fusion (EMFF) network structure, which first differentiates the inputs of the three feature layers and then ensures the effective flow between the original and enhanced features of each feature layer by two multiscale feature fusions as well as one diffusion. The experimental results demonstrate that the EMCF-RTDETR model improves the average precision mAP50 and mAP50:95 by 3.3% and 2.2%, respectively, compared to the RT-DETR model, and the FPS is improved by 10%. Moreover, our model outperforms other mainstream detection models in terms of accuracy and speed, revealing its significant potential for soybean weed detection. Full article

Soybeans are a major global commodity. A major challenge in soybean production is premature bean cracking, which leads to seed shedding and crop loss. Consistent breeding efforts are being made to minimize seed shedding in soybeans worldwide. Soybean breeding for increased abdominal suture strength has not resulted in varieties that are guaranteed to be resistant to premature cracking. Therefore, for further study of the issue, the study of the structural features of the soybean hilum is of practical interest. The trait of fusion of the seed hilum with the pod safe seeds from shedding. The paper presents studies of a soybean collection based on cracking features and resistance to seeds shedding. The largest number of cracking forms were found in the varieties of the first four maturity groups (000, 00, 0 and I). A positive correlation was observed between the cracking and non-shedding seeds traits (r = 0.48). The trait of fusion of the seed hilum with the pod valves turned out to be dominant. Our findings suggest that this trait may be influenced by a single gene or exhibit intermediate inheritance, but further genetic analysis is needed. The average yields of the control nursery numbers with a fused seed stalk (4.36 t/ha) are lower than the average yields of numbers without this trait (4.75 t/ha). Full article

Phytoalexins are specialized metabolites that are synthesized by plants in response to pathogens. A paradigm in transcription factor (TF) biology is that conserved TFs have dedicated roles across plant lineages in regulating specific branches of specialized metabolism. However, the Arabidopsis (Arabidopsis thaliana) NAC family TF ANAC042 (a.k.a. JUNGBRUNNEN1 or JUB1) regulates the synthesis of camalexin, a Trp-derived phytoalexin specifically produced by several Brassicaceae species, whereas its homolog in soybean (Glycine max) regulates the synthesis of glyceollins, which are Phe-derived phytoalexins specific to soybean. The question addressed by this research is whether ANAC042 broadly regulates phytoalexin biosynthetic pathways in Arabidopsis. Using a novel matrix-assisted laser desorption ionization high-resolution mass spectrometry (MALDI-HRMS) method, we found that the Arabidopsis loss-of-function mutant anac042–1 elicited with bacterial flagellin (Flg22) is deficient in lineage-specific Trp- and conserved Phe-derived phytoalexins—namely camalexin and 4-hydroxyindole-3-carbonyl nitrile (4OH-ICN), and pathogen-inducible monolignols and scopoletin, respectively. Overexpressing ANAC042 in the anac042-1 mutant restored or exceeded wildtype amounts of the metabolites. The expression of phytoalexin biosynthetic genes in mutant and overexpression lines mirrored the accumulation of metabolites. Yeast-one hybrid and promoter-reporter assays in Nicotiana benthamiana found that the ANAC042 protein directly binds and activates the promoters of CYP71B15, CYP71A12, and PAL1 genes for the synthesis of camalexin, 4OH-ICN, and pathogen-inducible monolignol/scopoletin, respectively. Our results demonstrate that ANAC042 regulates conserved and lineage-specific phytoalexin pathways in Arabidopsis. The latter suggests that it is an opportunistic TF that has coopted lineage-specific genes into phytoalexin metabolism, thus providing an exception to the current paradigm. Full article

Soy protein concentrate (SPC) is a cost-effective alternative to fish meal (FM) in aquaculture, but its deficiency in essential amino acids, particularly methionine, limits its application. This study evaluated the effects of methionine supplementation on growth, liver and intestinal health, and muscle quality in hybrid sturgeon (Acipenser baerii ♀ × A. schrenckii ♂) fed SPC-based diets. Four diets were formulated: an FM control diet, and SPC diets supplemented with 0% (M0), 0.25% (M2.5), and 0.50% (M5) methionine. Replacing FM with SPC without methionine (M0) significantly reduced weight gain and the protein efficiency ratio (PER) while increasing the feed conversion ratio (FCR) and hepatic lipid accumulation. Methionine supplementation (M5) restored growth performance, the PER, and muscle texture to levels comparable to the FM group. Intestinal enzyme activities (lipase and trypsin), villus height, and goblet cell counts significantly improved in the M5 group. Gene expression analysis showed that M5 upregulated tight junction genes (claudin1, occludin) and anti-inflammatory genes (tgfβ, lysozyme) while reducing pro-inflammatory cytokines (il1β, il8). In the liver, M5 reduced oxidative stress markers such as malondialdehyde (MDA) and improved antioxidant enzyme activities (SOD, CAT) while optimizing lipid metabolism, as evidenced by lower triglyceride (TG) and total cholesterol (TC) levels. Muscle quality analysis showed that M5 significantly increased muscle hardness, chewiness, and fiber density compared to M0. In conclusion, methionine supplementation at 0.50% effectively mitigates the negative effects of SPC, improving growth, liver and intestinal health, and muscle quality in hybrid sturgeon. Full article

The pseudo response regulator (PRR) gene is an important component of the core oscillator involved in plant circadian rhythms and plays an important role in regulating plant growth and development and stress responses. In this study, we investigated the function of GmPRR7b by overexpression and gene editing approaches. It was found that GmPRR7b plays a role in delaying flowering. While GmPRR7b overexpressing plants showed significantly delayed flowering compared to untransformed WT, GmPRR7b edited plants flowered earlier than the control WT. On the basis of previous research results and bioinformatics analysis, we re-identified 14 soybean PRR genes and analysed their rhythmic expression. Based on the rhythmic expression pattern, we found that GmPRR5/9a and GmPRR5/9b interacted with GmPRR7b by yeast two-hybrid and bimolecular fluorescence complementation (BiFC) experiments. Combined with the expression regulatory networks of the GmPRR7b, we inferred a possible regulatory mechanism by which GmPRR7b affects flowering through quit rhythm expression. These research elements provide valuable references for understanding growth, development, and circadian regulation in soybean. Full article

Understanding the ability of hybrids of genetically modified (GM) soybean and wild soybean to survive and reproduce under unfavorable conditions is critical for answering questions regarding risk assessment and the existence of transgenes in the environment. To investigate the effects of high-temperature stress on soybean growth and competitive ability, the GM soybean DBN8002, which expresses the VIP3Aa and PAT proteins, and F₂ generations derived from a cross between GM soybean and NJW (wild soybean) were placed in a greenhouse with an elevated temperature (38/32 °C) for 14 days, and the plant agronomic performance and foreign protein levels of hybrid soybean were evaluated to observe their responses to high temperature. The results revealed that the VIP3Aa and PAT protein levels in F₂ and GM were not influenced by high-temperature stress. In contrast, the pollen germination, pod number, hundred-seed weight, and seed vigor of the F₂ hybrid and parent soybean plants decreased after high-temperature stress. However, except for the number of fully filled seeds per plant, the above parameters of the F₂ hybrid were similar to or slightly lower than those of wild soybean, and no significant difference in fitness was observed between the F₂ hybrid and wild soybean, indicating that the growth and competitive ability of the hybrid were similar to those of its female parent under heat stress conditions, resulting in the transgenes persisting and spreading within agricultural ecosystems. Our results enhance the understanding of the GM soybean plant’s response to heat stress, lay the foundation for breeding heat-resistant soybean varieties, and provide new insights and advanced information on the ecological risks arising from the escape of transgenes. Full article

Phytophthora root and stem rot caused by Phytophthora sojae (P. sojae) is a globally prevalent oomycete disease. The use of resistant cultivars is an effective and environmentally friendly strategy to manage this disease. It is important to understand the molecular mechanisms underlying the response of Glycine max (soybean) to P. sojae infection. In this study, we demonstrated that an isoflavonoid-specific prenyltransferase gene (GmPT10d, Glyma.10G070300) was significantly upregulated in the soybean cultivar Williams 82 with high resistance to P. sojae infection. Transgenic soybean seedlings overexpressing GmPT10d exhibited enhanced resistance to P. sojae, and those subjected to RNA interference showed increased susceptibility to the pathogen. Yeast-one-hybrid and electrophoretic mobility shift assays revealed that GmARF15 could directly bind to the promoter of GmPT10d. Further analysis of the GmARF15 function showed that transgenic soybean seedlings overexpressing GmARF15 also exhibited enhanced resistance to P. sojae. Transactivation assay, luciferase assay, and qPCR analysis showed that GmARF15 could promote the expression of GmPT10d. Further analysis indicated that elevated salicylic acid levels were associated with increased expression of GmARF15 and GmPT10d. Taken together, these findings reveal a regulatory mechanism by which GmARF15 enhances soybean resistance to P. sojae, potentially by promoting the expression of GmPT10d through the salicylic acid signaling pathway. Full article

Soybean yield prediction is one of the most critical activities for increasing agricultural productivity and ensuring food security. Traditional models often underestimate yields because of limitations associated with single data sources and simplistic model architectures. These prevent complex, multifaceted factors influencing crop growth and yield from being captured. In this line, this work fuses multi-source data—satellite imagery, weather data, and soil properties—through the approach of multi-modal fusion using Convolutional Neural Networks and Recurrent Neural Networks. While satellite imagery provides information on spatial data regarding crop health, weather data provides temporal insights, and the soil properties provide important fertility information. Fusing these heterogeneous data sources embeds an overall understanding of yield-determining factors in the model, decreasing the RMSE by 15% and improving R² by 20% over single-source models. We further push the frontier of feature engineering by using Temporal Convolutional Networks (TCNs) and Graph Convolutional Networks (GCNs) to capture time series trends, geographic and topological information, and pest/disease incidence. TCNs can capture long-range temporal dependencies well, while the GCN model has complex spatial relationships and enhanced the features for making yield predictions. This increases the prediction accuracy by 10% and boosts the F1 score for low-yield area identification by 5%. Additionally, we introduce other improved model architectures: a custom UNet with attention mechanisms, Heterogeneous Graph Neural Networks (HGNNs), and Variational Auto-encoders. The attention mechanism enables more effective spatial feature encoding by focusing on critical image regions, while the HGNN captures interaction patterns that are complex between diverse data types. Finally, VAEs can generate robust feature representation. Such state-of-the-art architectures could then achieve an MAE improvement of 12%, while R² for yield prediction improves by 25%. In this paper, the state of the art in yield prediction has been advanced due to the employment of multi-source data fusion, sophisticated feature engineering, and advanced neural network architectures. This provides a more accurate and reliable soybean yield forecast. Thus, the fusion of Convolutional Neural Networks with Recurrent Neural Networks and Graph Networks enhances the efficiency of the detection process. Full article

Seed protein content is a critical trait in soybean breeding, as it provides a primary source of high-quality protein for both human consumption and animal feed. This study aimed to enhance molecular marker-assisted selection for high-protein soybean varieties by developing Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) markers targeted at loci associated with seed protein content. Nineteen markers with high genotyping efficacy were identified through screening. Utilizing SN76 (a high-protein line) as the male parent and SN49 and DS1 (both low-protein lines) as female parents, 484 F₆ generation individuals from these hybrid combinations were selected to validate the predictive accuracy of the 19 KASP markers. Notably, KASP-Pro-1, KASP-Pro-2, and KASP-Pro-3 effectively distinguished genotypes associated with high and low protein content, with prediction accuracies of 68.4%, 75.0%, and 83.3%, respectively. These results underscore the reliability and practical utility of the selected molecular markers, which are located within the genes Glyma.03G219900, Glyma.14G119000, and Glyma.17G074400, respectively. Haplotype analysis and gene pyramiding indicate that these three genes may influence seed protein content. Consequently, these KASP markers can be effectively integrated into genetic and genomic research on soybean seed protein content as well as into marker-assisted breeding. Full article