A transformer-based genomic prediction method fused with knowledge-guided module.

Genomic prediction (GP) uses single nucleotide polymorphisms (SNPs) to establish associations between markers and phenotypes. Selection of early individuals by genomic estimated breeding value shortens the generation interval and speeds up the breeding process. Recently, methods based on deep learning (DL) have gained great attention in the field of GP. In this study, we explore the application of Transformer-based structures to GP and develop a novel deep-learning model named GPformer. GPformer obtains a global view by gleaning beneficial information from all relevant SNPs regardless of the physical distance between SNPs. Comprehensive experimental results on five different crop datasets show that GPformer outperforms ridge regression-based linear unbiased prediction (RR-BLUP), support vector regression (SVR), light gradient boosting machine (LightGBM) and deep neural network genomic prediction (DNNGP) in terms of mean absolute error, Pearson's correlation coefficient and the proposed metric consistent index. Furthermore, we introduce a knowledge-guided module (KGM) to extract genome-wide association studies-based information, which is fused into GPformer as prior knowledge. KGM is very flexible and can be plugged into any DL network. Ablation studies of KGM on three datasets illustrate the efficiency of KGM adequately. Moreover, GPformer is robust and stable to hyperparameters and can generalize to each phenotype of every dataset, which is suitable for practical application scenarios.

Identification of QTLs and candidate genes for water-soluble protein content in soybean seeds.

Soybean represents a vital source of premium plant-based proteins for human nutrition. Importantly, the level of water-soluble protein (WSP) is crucial for determining the overall quality and nutritional value of such crops. Enhancing WSP levels in soybean plants is a high-priority goal in crop improvement. This study aimed to elucidate the genetic basis of WSP content in soybean seeds by identifying quantitative trait loci (QTLs) and set the foundation for subsequent gene cloning and functional analysis. Using 180 F10 recombinant inbred lines generated by crossing the high-protein soybean cultivar JiDou 12 with the wild variety Ye 9, our researcher team mapped the QTLs influencing protein levels, integrating Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene expression profiling to identify candidate genes. During the 2020 and 2022 growing seasons, a standard bell-shaped distribution of protein content trait data was observed in these soybean lines. Eight QTLs affecting protein content were found across eight chromosomes, with LOD scores ranging from 2.59 to 7.30, explaining 4.15-11.74% of the phenotypic variance. Notably, two QTLs were newly discovered, one with a elite allele at qWSPC-15 from Ye 9. The major QTL, qWSPC-19, on chromosome 19 was stable across conditions and contained genes involved in nitrogen metabolism, amino acid biosynthesis, and signaling. Two genes from this QTL, Glyma.19G185700 and Glyma.19G186000, exhibited distinct expression patterns at maturity, highlighting the influence of these genes on protein content. This research revealed eight QTLs for WSP content in soybean seeds and proposed a gene for the key QTL qWSPC-19, laying groundwork for gene isolation and enhanced soybean breeding through the use of molecular markers. These insights are instrumental for developing protein-rich soybean cultivars.

From Sheep Track to Motorway: Supramolecular-Mediated 2D Nanofluidic Channels for Ultrafast Water Transport.

Atomic thick 2D materials hold great potential as building blocks to construct highly permeable membranes, yet the permeability of laminar 2D material membranes is still limited by their irregularity sheep track-like interlayer channels. Herein, a supramolecular-mediated strategy to induce the regular assembly of high-throughput 2D nanofluidic channels based on host-guest interactions is proposed. Inspired by the characteristics of motorways, supramolecular-mediated ultrathin 2D membranes with broad and continuous regular water transport channels are successfully constructed using graphene oxide (GO) as an example. The prepared membrane achieves an ultrahigh water permeability (369.94 LMH bar-1) more than six times higher than that of the original membranes while maintaining dye rejection above 98.5%, which outperforms the reported 2D membranes. Characterization and simulation results show that the introduction of hyaluronate-grafted ß-cyclodextrin not only expands the interlayer channels of GO membranes but also enables the membranes to operate stably under harsh conditions with the help of host-guest interactions. This universal supramolecular assembly strategy provides new opportunities for the preparation of 2D membranes with high separation performance and reliable and stable nanofluidic channels.

Cold tolerance SNPs and candidate gene mining in the soybean germination stage based on genome-wide association analysis.

KEY MESSAGE: Three QTLs associated with low-temperature tolerance were identified by genome-wide association analysis, and 15 candidate genes were identified by haplotype analysis and gene expression analyses. Low temperature is a critical factor affecting the geographical distribution, growth, development, and yield of soybeans, with cold stress during seed germination leading to substantial productivity loss. In this study, an association panel comprising 260 soybean accessions was evaluated for four germination traits and four cold tolerance index traits, revealing extensive variation in cold tolerance. Genome-wide association study (GWAS) identified 10 quantitative trait nucleotides (QTNs) associated with cold tolerance, utilizing 30,799 single nucleotide polymorphisms (SNPs) and four GWAS models. Linkage disequilibrium (LD) analysis positioned these QTNs within three cold-tolerance quantitative trait loci (QTL) and, with QTL19-1, was positioned by three multi-locus models, underscoring its importance as a key QTL. Integrative haplotype analysis, supplemented by transcriptome analysis, uncovered 15 candidate genes. The haplotypes within the genes Glyma.18G044200, Glyma.18G044300, Glyma.18G044900, Glyma.18G045100, Glyma.19G222500, and Glyma.19G222600 exhibited significant phenotypic variations, with differential expression in materials with varying cold tolerance. The QTNs and candidate genes identified in this study offer substantial potential for marker-assisted selection and gene editing in breeding cold-tolerant soybeans, providing valuable insights into the genetic mechanisms underlying cold tolerance during soybean germination.

Fe-Co Co-Doped 1D@2D Carbon-Based Composite as an Efficient Catalyst for Zn-Air Batteries.

A Fe-Co dual-metal co-doped N containing the carbon composite (FeCo-HNC) was prepared by adjusting the ratio of iron to cobalt as well as the pyrolysis temperature with the assistance of functionalized silica template. Fe1Co-HNC, which was formed with 1D carbon nanotubes and 2D carbon nanosheets including a rich mesoporous structure, exhibited outstanding oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) catalytic activities. The ORR half-wave potential is 0.86 V (vs. reversible hydrogen electrode, RHE), and the OER overpotential is 0.76 V at 10 mA cm-2 with the Fe1Co-HNC catalyst. It also displayed superior performance in zinc-air batteries. This method provides a promising strategy for the fabrication of efficient transition metal-based carbon catalysts.

BTA2 regulates tiller angle and the shoot gravity response through controlling auxin content and distribution in rice.

Tiller angle is a key agricultural trait that establishes plant architecture, which in turn strongly affects grain yield by influencing planting density in rice. The shoot gravity response plays a crucial role in the regulation of tiller angle in rice, but the underlying molecular mechanism is largely unknown. Here, we report the identification of the BIG TILLER ANGLE2 (BTA2), which regulates tiller angle by controlling the shoot gravity response in rice. Loss-of-function mutation of BTA2 dramatically reduced auxin content and affected auxin distribution in rice shoot base, leading to impaired gravitropism and therefore a big tiller angle. BTA2 interacted with AUXIN RESPONSE FACTOR7 (ARF7) to modulate rice tiller angle through the gravity signaling pathway. The BTA2 protein was highly conserved during evolution. Sequence variation in the BTA2 promoter of indica cultivars harboring a less expressed BTA2 allele caused lower BTA2 expression in shoot base and thus wide tiller angle during rice domestication. Overexpression of BTA2 significantly increased grain yield in the elite rice cultivar Huanghuazhan under appropriate dense planting conditions. Our findings thus uncovered the BTA2-ARF7 module that regulates tiller angle by mediating the shoot gravity response. Our work offers a target for genetic manipulation of plant architecture and valuable information for crop improvement by producing the ideal plant type.

Asymmetric C3-Allylation of Pyridines.

Asymmetric intermolecular C-H functionalization of pyridines at C3 is unprecedented. Herein, we report the first examples of such transformations: specifically, C3-allylation of pyridines via tandem borane and iridium catalysis. First, borane-catalyzed pyridine hydroboration generates nucleophilic dihydropyridines; then, the dihydropyridine undergoes enantioselective iridium-catalyzed allylation; and finally, oxidative aromatization with air as the oxidant gives the C3-allylated pyridine. This protocol provides direct access to C3-allylated pyridines with excellent enantioselectivity (up to >99% ee) and is suitable for late-stage functionalization of pyridine-containing drugs.

Integrating genome-wide association study into genomic selection for the prediction of agronomic traits in rice (Oryza sativa L.).

Accurately identifying varieties with targeted agronomic traits was thought to contribute to genetic selection and accelerate rice breeding progress. Genomic selection (GS) is a promising technique that uses markers covering the whole genome to predict the genomic-estimated breeding values (GEBV), with the ability to select before phenotypes are measured. To choose the appropriate GS models for breeding work, we analyzed the predictability of nine agronomic traits measured from a population of 459 diverse rice varieties. By the comparison of eight representative GS models, we found that the prediction accuracies ranged from 0.407 to 0.896, with reproducing kernel Hilbert space (RKHS) having the highest predictive ability in most traits. Further results demonstrated the predictivity of GS is altered by several factors. Moreover, we assessed the method of integrating genome-wide association study (GWAS) into various GS models. The predictabilities of GS combined peak-associated markers generated from six different GWAS models were significantly different; a recommendation of Mixed Linear Model (MLM)-RKHS was given for the GWAS-GS-integrated prediction. Finally, based on the above result, we experimented with applying the P-values obtained from optimal GWAS models into ridge regression best linear unbiased prediction (rrBLUP), which benefited the low predictive traits in rice. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01423-y.

Development of SNP marker panels for genotyping by target sequencing (GBTS) and its application in soybean.

A high-throughput genotyping platform with customized flexibility, high genotyping accuracy, and low cost is critical for marker-assisted selection and genetic mapping in soybean. Three assay panels were selected from the SoySNP50K, 40K, 20K, and 10K arrays, containing 41,541, 20,748, and 9670 SNP markers, respectively, for genotyping by target sequencing (GBTS). Fifteen representative accessions were used to assess the accuracy and consistency of the SNP alleles identified by the SNP panels and sequencing platform. The SNP alleles were 99.87% identical between technical replicates and 98.86% identical between the 40K SNP GBTS panel and 10× resequencing analysis. The GBTS method was also accurate in the sense that the genotypic dataset of the 15 representative accessions correctly revealed the pedigree of the accessions, and the biparental progeny datasets correctly constructed the linkage maps of the SNPs. The 10K panel was also used to genotype two parent-derived populations and analyze QTLs controlling 100-seed weight, resulting in the identification of the stable associated genetic locus Locus_OSW_06 on chromosome 06. The markers flanking the QTL explained 7.05% and 9.83% of the phenotypic variation, respectively. Compared with GBS and DNA chips, the 40K, 20K, and 10K panels reduced costs by 5.07% and 58.28%, 21.44% and 65.48%, and 35.74% and 71.76%, respectively. Low-cost genotyping panels could facilitate soybean germplasm assessment, genetic linkage map construction, QTL identification, and genomic selection. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01372-6.

Transcriptome mapping related genes encoding PR1 protein involved in necrotic symptoms to soybean mosaic virus infection.

Necrosis caused by soybean mosaic virus (SMV) has not been specifically distinguished from susceptible symptoms. The molecular mechanism for the occurrence of necrosis is largely overlooked in soybean genetic research. Field evaluation reveals that SMV disease seriously influences soybean production as indicated by decreasing 22.4% ~ 77.0% and 8.8% ~ 17.0% of yield and quality production, respectively. To expand molecular mechanism behind necrotic reactions, transcriptomic data obtained from the asymptomatic, mosaic, and necrotic pools were assessed. Compared between asymptomatic and mosaic plants, 1689 and 1752 up- and down-regulated differentially expressed genes (DEGs) were specifically found in necrotic plants. Interestingly, the top five enriched pathways with up-regulated DEGs were highly related to the process of the stress response, whereas the top three enriched pathways with down-regulated DEGs were highly related to the process of photosynthesis, demonstrating that defense systems are extensively activated, while the photosynthesis systems were severely destroyed. Further, results of the phylogenetic tree based on gene expression pattern and an amino acid sequence and validation experiments discovered three PR1 genes, Glyma.15G062400, Glyma.15G062500, and Glyma.15G062700, which were especially expressed in necrotic leaves. Meanwhile, exogenous salicylic acid (SA) but not methyl jasmonate (MeJA) could induce the three PR1 gene expressions on healthy leaves. Contrastingly, exogenous SA obviously decreased the expression level of Glyma.15G062400, Glyma.15G062500, and concentration of SMV, but increased Glyma.15G062700 expression in necrotic leaves. These results showed that GmPR1 is associated with the development of SMV-induced necrotic symptoms in soybean. Glyma.15G062400, Glyma.15G062500, and Glyma.15G062700 is up-regulated in necrotic leaves at the transcriptional levels, which will greatly facilitate a better understanding of the mechanism behind necrosis caused by SMV disease. Supplementary information: The online version contains supplementary material available at 10.1007/s11032-022-01351-3.

Genomic insight into genetic changes and shaping of major inbred rice cultivars in China.

The annual planting area of major inbred rice (Oryza sativa) cultivars reach more than half of the total annual planting area of inbred rice cultivars in China. However, how the major inbred rice cultivars changed during decades of genetic improvement and why they can be prevalently cultivated in China remains unclear. Here, we investigated the underlying genetic changes of major inbred cultivars and the contributions of landraces and introduced cultivars during the improvement by resequencing a collection of 439 rice accessions including major inbred cultivars, landraces, and introduced cultivars. The results showed that landraces were the main genetic contribution sources of major inbred Xian (Indica) cultivars, while introduced cultivars were that of major inbred Geng (Japonica) cultivars. Selection scans and haplotype frequency analysis shed light on the reflections of some well-known genes in rice improvement, and breeders had different preferences for the Xian's and Geng's breeding. Six candidate regions associated with agronomic traits were identified by genome-wide association mapping, five of which were under positive selection in rice improvement. Our study provides a comprehensive insight into the development of major inbred rice cultivars and lays the foundation for genomics-based breeding in rice.

Intestinal fibrosis classification in patients with Crohn's disease using CT enterography-based deep learning: comparisons with radiomics and radiologists.

OBJECTIVES: Accurate evaluation of bowel fibrosis in patients with Crohn's disease (CD) remains challenging. Computed tomography enterography (CTE)-based radiomics enables the assessment of bowel fibrosis; however, it has some deficiencies. We aimed to develop and validate a CTE-based deep learning model (DLM) for characterizing bowel fibrosis more efficiently. METHODS: We enrolled 312 bowel segments of 235 CD patients (median age, 33 years old) from three hospitals in this retrospective study. A training cohort and test cohort 1 were recruited from center 1, while test cohort 2 from centers 2 and 3. All patients performed CTE within 3 months before surgery. The histological fibrosis was semi-quantitatively assessed. A DLM was constructed in the training cohort based on a 3D deep convolutional neural network with 10-fold cross-validation, and external independent validation was conducted on the test cohorts. The radiomics model (RM) was developed with 4 selected radiomics features extracted from CTE images by using logistic regression. The evaluation of CTE images was performed by two radiologists. DeLong's test and a non-inferiority test were used to compare the models' performance. RESULTS: DLM distinguished none-mild from moderate-severe bowel fibrosis with an area under the receiver operator characteristic curve (AUC) of 0.828 in the training cohort and 0.811, 0.808, and 0.839 in the total test cohort, test cohorts 1 and 2, respectively. In the total test cohort, DLM achieved better performance than two radiologists (*1 AUC = 0.579, *2 AUC = 0.646; both p < 0.05) and was not inferior to RM (AUC = 0.813, p < 0.05). The total processing time for DLM was much shorter than that of RM (p < 0.001). CONCLUSION: DLM is better than radiologists in diagnosing intestinal fibrosis on CTE in patients with CD and not inferior to RM; furthermore, it is more time-saving compared to RM. KEY POINTS: • Question Could computed tomography enterography (CTE)-based deep learning model (DLM) accurately distinguish intestinal fibrosis severity in patients with Crohn's disease (CD)? • Findings In this cross-sectional study that included 235 patients with CD, DLM achieved better performance than that of two radiologists' interpretation and was not inferior to RM with significant differences and much shorter processing time. • Meaning This DLM may accurately distinguish the degree of intestinal fibrosis in patients with CD and guide gastroenterologists to formulate individualized treatment strategies for those with bowel strictures.

Porous materials formed by four self-construction processes.

Multiple self-construction behavior of cyclic oligoesters is described. Rigid braces and elastic hinges are periodically incorporated into these cyclomers, which enables these rings to form various topological frameworks, such as holes, caves or cages with different sizes and shapes, through self-folding. Among them, the cave-type cyclomer self-assembles into nanotunnels and then forms porous materials via self-packing of these tunnels. This discovery provides a new perspective for the construction of novel materials aided by multiple supramolecular effects. In this work, the simplest rigid brace components and ones with soft hinges were chosen to construct cyclomers to confirm the supramolecular strategy.

Identification of Novel Genomic Regions for Bacterial Leaf Pustule (BLP) Resistance in Soybean (Glycine max L.) via Integrating Linkage Mapping and Association Analysis.

Bacterial leaf pustule (BLP), caused by Xanthornonas axonopodis pv. glycines (Xag), is a worldwide disease of soybean, particularly in warm and humid regions. To date, little is known about the underlying molecular mechanisms of BLP resistance. The only single recessive resistance gene rxp has not been functionally identified yet, even though the genotypes carrying the gene have been widely used for BLP resistance breeding. Using a linkage mapping in a recombinant inbred line (RIL) population against the Xag strain Chinese C5, we identified that quantitative trait locus (QTL) qrxp-17-2 accounted for 74.33% of the total phenotypic variations. We also identified two minor QTLs, qrxp-05-1 and qrxp-17-1, that accounted for 7.26% and 22.26% of the total phenotypic variations, respectively, for the first time. Using a genome-wide association study (GWAS) in 476 cultivars of a soybean breeding germplasm population, we identified a total of 38 quantitative trait nucleotides (QTNs) on chromosomes (Chr) 5, 7, 8, 9,15, 17, 19, and 20 under artificial infection with C5, and 34 QTNs on Chr 4, 5, 6, 9, 13, 16, 17, 18, and 20 under natural morbidity condition. Taken together, three QTLs and 11 stable QTNs were detected in both linkage mapping and GWAS analysis, and located in three genomic regions with the major genomic region containing qrxp_17_2. Real-time RT-PCR analysis of the relative expression levels of five potential candidate genes in the resistant soybean cultivar W82 following Xag treatment showed that of Glyma.17G086300, which is located in qrxp-17-2, significantly increased in W82 at 24 and 72 h post-inoculation (hpi) when compared to that in the susceptible cultivar Jack. These results indicate that Glyma.17G086300 is a potential candidate gene for rxp and the QTLs and QTNs identified in this study will be useful for marker development for the breeding of Xag-resistant soybean cultivars.

[Quality evaluation of Ginseng Radix et Rhizoma based on UPLC characteristic chromatogram and quantitative analysis of multi-components by single marker (QAMS)].

Based on UPLC characteristic chromatogram and quantitative analysis of multi-components by single marker(QAMS), the content of seven types of ginsenosides in Ginseng Radix et Rhizoma was simultaneously determined, and the quality of Ginseng Radix et Rhizoma was evaluated by the principal component analysis(PCA). The chromatographic separation was performed on the Acquity UPLC BEH C_(18) column(2.1 mm×100 mm, 1.7 µm) with the mobile phase of acetonitrile-water for gradient elution at the flow rate of 0.3 mL·min~(-1), the column temperature of 30 ℃, the detection wavelength of 203 nm, and the injection volume of 2 µL. The UPLC chromatogram was established with 19 batches of Ginseng Radix et Rhizoma samples from three producing areas by Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(version 2012). Thirteen characteristic peaks were determined and seven components were identified. SPSS 26.0 was used to conduct PCA on the characteristic peak areas. With the peak of ginsenoside Rb_1 as reference peak S, ginsenoside Rb_1 showed good durability of relative correction factor as compared with other ginsenosides. The QAMS method for the determination of seven ginsenosides in Ginseng Radix et Rhizoma was established. There was no significant difference in results between the QAMS method and the external standard method. As revealed by the results of PCA and the determination of the total content of seven ginsenosides, the four batches of Ginseng Radix et Rhizoma numbered S19, S18, S1, and S2 were of superior quality. The characteristic chromatogram and QAMS method for the determination of seven ginsenosides in this study were convenient and accurate, which greatly shortened the analysis time and improved the analysis efficiency. The findings of this study are expected to provide a basis for the overall quality evaluation of Ginseng Radix et Rhizoma.

Discovery of a potent ß-catenin destabilizer for overcoming the resistance of 5-fluorouracil in colorectal cancer.

Wnt/ß-catenin signalling is frequently activated in colorectal cancer, in which nuclear ß-catenin accumulation contributes to tumour initiation and progression. However, therapeutic agents in clinical use targeting this pathway are lacking. In this report, we describe the synthesis of novel stemona alkaloid analogues and their biological evaluation, among which compound 3 was identified to efficiently inhibit various CRC cells, including 5-fluorouracil-resistant CRC cells. Mechanistically, this study revealed that compound 3 reduced the protein level of ß-catenin without affecting its mRNA level, which suggests an alternative mechanism for ß-catenin degradation. The expression of downstream proteins, including c-myc, survivin, and cyclin D1, was also significantly inhibited, even in Wnt-activated CRC cells. Briefly, our data highlight the potential of compound 3 as a destabilizer of ß-catenin for the treatment of CRC patients.

Engineering Thermotoga maritima ß-glucosidase for improved alkyl glycosides synthesis by site-directed mutagenesis.

Alkyl glycosides are well-characterized nonionic surfactants, and can be prepared by transglycosylation reactions with retaining GH1 glycosidases being normally used for this purpose. The produced alkyl glycosides can also be hydrolyzed by the glycosidase, and hence, the yields of alkyl glycosides can be too low for industrial use. To improve the transglycosylation-to-hydrolysis ratio for a ß-glucosidase from Thermotoga maritima (TmBglA) for the synthesis of alkyl glycoside, six mutants (N222F, N223C, N223Q, G224A, Y295F, and F414S) were produced. N222F, N223C, N223Q, G224A improved catalytic activity, F295Y and F414S are hydrolytically crippled with p-nitrophenol-ß-d-glucopyranoside (pNPG) as substrate with an 85 and 70-fold decrease in apparent kcat, respectively; N222F shows the highest kcat/km value for pNPG. The substrate selectivity altered from pNPG to pNP-ß-d-fucoside for N222F, F295Y, and F414S and from cellubiose to gentiobiose for N222F and F414S. Using pNPG (34 mM) and hexanol 80% (vol/vol), N222F, Y295F, and F414S synthesized hexyl-ß-glycoside (HG) yields of 84.7%, 50.9%, and 54.1%, respectively, HG increased from 14.49 (TmBglA) to 22.8 mM (N222F) at 2 hr by 57.42%. However, this higher transglycosylation effect depended on that three mutants creates an environment more suited for hexanol in the active site pocket, and consequently suppressed its HG hydrolysis.

Molecular Bridges Stabilize Graphene Oxide Membranes in Water.

Recent innovations highlight the great potential of two-dimensional graphene oxide (GO) films in water-related applications. However, undesirable water-induced effects, such as the redispersion and peeling of stacked GO laminates, greatly limit their performance and impact their practical application. It remains a great challenge to stabilize GO membranes in water. A molecular bridge strategy is reported in which an interlaminar short-chain molecular bridge generates a robust GO laminate that resists the tendency to swell. Furthermore, an interfacial long-chain molecular bridge adheres the GO laminate to a porous substrate to increase the mechanical strength of the membrane. By rationally creating and tuning the molecular bridges, the stabilized GO membranes can exhibit outstanding durability in harsh operating conditions, such as cross-flow, high-pressure, and long-term filtration. This general and scalable stabilizing approach for GO membranes provides new opportunities for reliable two-dimensional laminar films used in aqueous environments.

Genetic improvement of the shoot architecture and yield in soya bean plants via the manipulation of GmmiR156b.

The optimization of plant architecture in order to breed high-yielding soya bean cultivars is a goal of researchers. Tall plants bearing many long branches are desired, but only modest success in reaching these goals has been achieved. MicroRNA156 (miR156)-SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) gene modules play pivotal roles in controlling shoot architecture and other traits in crops like rice and wheat. However, the effects of miR156-SPL modules on soya bean architecture and yield, and the molecular mechanisms underlying these effects, remain largely unknown. In this study, we achieved substantial improvements in soya bean architecture and yield by overexpressing GmmiR156b. Transgenic plants produced significantly increased numbers of long branches, nodes and pods, and they exhibited an increased 100-seed weight, resulting in a 46%-63% increase in yield per plant. Intriguingly, GmmiR156b overexpression had no significant impact on plant height in a growth room or under field conditions; however, it increased stem thickness significantly. Our data indicate that GmmiR156b modulates these traits mainly via the direct cleavage of SPL transcripts. Moreover, we found that GmSPL9d is expressed in the shoot apical meristem and axillary meristems (AMs) of soya bean, and that GmSPL9d may regulate axillary bud formation and branching by physically interacting with the homeobox gene WUSCHEL (WUS), a central regulator of AM formation. Together, our results identify GmmiR156b as a promising target for the improvement of soya bean plant architecture and yields, and they reveal a new and conserved regulatory cascade involving miR156-SPL-WUS that will help researchers decipher the genetic basis of plant architecture.

Folate-Conjugated Cell Membrane Mimetic Polymer Micelles for Tumor-Cell-Targeted Delivery of Doxorubicin.

Tumor-targeting nano-drug-delivery systems hold great potential to improve the therapeutic efficacy and alleviate the side effects of cancer treatments. Herein, folic acid (FA)-decorated amphiphilic copolymer of FA-P(MPC- co-MaPCL) (MPC: 2-methacryloxoethyl phosphorylcholine, MaPCL: poly(ε-caprolactone) macromonomer) is synthesized and its micelles are fabricated for doxorubicin (DOX) delivery. And non-FA-decorated P(MPC- co-MaPCL) micelles are used as the control. Dynamic light scattering and scanning electron microscopy measurements reveal that FA-P(MPC- co-MaPCL) and P(MPC- co-MaPCL) micelles are spherical with average diameters of 140 and 90 nm, respectively. The evaluation in vitro demonstrates that the blank micelles are nontoxic, while DOX-loaded FA-P(MPC- co-MaPCL) micelles show significant cytotoxicity to HeLa cells and slight cytotoxicity to L929 cells. Moreover, the cellular uptake of DOX-loaded FA-P(MPC- co-MaPCL) micelles in HeLa cells are 4.3-fold and 1.7-fold higher than that of DOX-loaded P(MPC- co-MaPCL) micelles and free DOX after 6 h of incubation, respectively. These results indicate the great potential of this system in anticancer target drug-delivery applications.