PLAU promotes cell proliferation and migration of head and neck cancer via STAT3 signaling pathway.

It was reported that within the head and neck cancer (HNC) cell line CAL21 the epithelial-mesenchymal transition (EMT) and cell proliferation were promoted by Urokinase-Type Plasminogen Activator (PLAU) proteinase through TNFRSF12A. Additionally, in this paper HNC cell lines refer to Fadu and Tu686. A novel PLAU-STAT3 axis was found to be involved in HNC cell line proliferation and metastasis. PLAU expression in HNC samples was upregulated, besides, the elevated expression of PLAU was linked to the lower overall survival (OS) and disease-free survival (DFS). Ectopic PLAU expression promoted cell proliferation and migration, while PLAU knockdown exhibited opposite results. RNA-seq data identified the JAK-STAT signaling pathway, confirmed by western blotting. A recovery assay using S3I-201, a selective inhibitor of signal transducer and activator of transcription 3 (STAT3), indicated that PLAU promoted HNC cell line progression via STAT3 signaling in vitro. The oncogenic role of PLAU in HNC tumor growth in vivo was confirmed using xenograft models. In summary, we identified the tumorigenic PLAU function in the HNC progress. PLAU may represent a potential prognostic biomarker of HNC and the PLAU-STAT3 pathway might be considered a therapeutic target of HNC.

Reciprocal adaptation of rice and Xanthomonas oryzae pv. oryzae: cross-species 2D GWAS reveals the underlying genetics.

A 1D/2D genome-wide association study strategy was adopted to investigate the genetic systems underlying the reciprocal adaptation of rice (Oryza sativa) and its bacterial pathogen, Xanthomonas oryzae pv. oryzae (Xoo) using the whole-genome sequencing and large-scale phenotyping data of 701 rice accessions and 23 diverse Xoo strains. Forty-seven Xoo virulence-related genes and 318 rice quantitative resistance genes (QR-genes) mainly located in 41 genomic regions, and genome-wide interactions between the detected virulence-related genes and QR genes were identified, including well-known resistance genes/virulence genes plus many previously uncharacterized ones. The relationship between rice and Xoo was characterized by strong differentiation among Xoo races corresponding to the subspecific differentiation of rice, by strong shifts toward increased resistance/virulence of rice/Xoo populations and by rich genetic diversity at the detected rice QR-genes and Xoo virulence genes, and by genome-wide interactions between many rice QR-genes and Xoo virulence genes in a multiple-to-multiple manner, presumably resulting either from direct protein-protein interactions or from genetic epistasis. The observed complex genetic interaction system between rice and Xoo likely exists in other crop-pathogen systems that would maintain high levels of diversity at their QR-loci/virulence-loci, resulting in dynamic coevolutionary consequences during their reciprocal adaptation.

CancerMIRNome: an interactive analysis and visualization database for miRNome profiles of human cancer.

MicroRNAs (miRNAs), which play critical roles in gene regulatory networks, have emerged as promising diagnostic and prognostic biomarkers for human cancer. In particular, circulating miRNAs that are secreted into circulation exist in remarkably stable forms, and have enormous potential to be leveraged as non-invasive biomarkers for early cancer detection. Novel and user-friendly tools are desperately needed to facilitate data mining of the vast amount of miRNA expression data from The Cancer Genome Atlas (TCGA) and large-scale circulating miRNA profiling studies. To fill this void, we developed CancerMIRNome, a comprehensive database for the interactive analysis and visualization of miRNA expression profiles based on 10 554 samples from 33 TCGA projects and 28 633 samples from 40 public circulating miRNome datasets. A series of cutting-edge bioinformatics tools and machine learning algorithms have been packaged in CancerMIRNome, allowing for the pan-cancer analysis of a miRNA of interest across multiple cancer types and the comprehensive analysis of miRNome profiles to identify dysregulated miRNAs and develop diagnostic or prognostic signatures. The data analysis and visualization modules will greatly facilitate the exploit of the valuable resources and promote translational application of miRNA biomarkers in cancer. The CancerMIRNome database is publicly available at http://bioinfo.jialab-ucr.org/CancerMIRNome.

Bioactivities and chemical profiling comparison and metabolomic variations of polyphenolics and steroidal glycoalkaloids in different parts of Solanum nigrum L.

INTRODUCTION: Solanum nigrum L. is a traditional medicinal herb and edible plant. Many studies provide evidence that S. nigrum L. is a nutritious vegetable. Polyphenols and steroidal glycoalkaloids are the main components. OBJECTIVES: This study aimed to systemically evaluate the phytochemical profile, quantification, and bioactivities of polyphenolics and glycoalkaloids in different parts of S. nigrum L. RESULTS: Total polyphenols (TPC) and total glycoalkaloids (TGK) were determined using the Folin-Ciocalteu and acid dye colorimetric methods, respectively. A total of 55 polyphenolic constituents (including 22 phenolic acids and 33 flavonoids) and 24 steroidal glycoalkaloids were identified from different parts using ultrahigh-performance liquid chromatography Q-exactive high-resolution mass spectrometry (UHPLC-QE-HRMS), of which 40 polyphenols (including 15 phenolic acids and 25 flavonoids) and one steroidal glycoalkaloid were characterised for the first time in S. nigrum L. Moreover, typical polyphenols and glycoalkaloids were determined using HPLC-UV and HPLC-evaporative light-scattering detector (ELSD), respectively. In addition, the TPC and TGK and their typical constituents were compared in different anatomical parts. Finally, the antioxidant capacities of polyphenolic extracts from different parts of S. nigrum L. were evaluated by ·OH, 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and ferric-reducing antioxidant power (FRAP) assay in vitro. In addition, the antitumour effects of TGK from different parts of S. nigrum L. on the proliferation of PC-3 cells were investigated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Polyphenolic and glycoalkaloid extracts from different parts of S. nigrum L. showed different antioxidant and cytotoxic capacities in vitro. CONCLUSION: This is the first study to systematically differentiate between polyphenolic and glycoalkaloid profiles from different parts of S. nigrum L.

Boosting predictabilities of agronomic traits in rice using bivariate genomic selection.

The multivariate genomic selection (GS) models have not been adequately studied and their potential remains unclear. In this study, we developed a highly efficient bivariate (2D) GS method and demonstrated its significant advantages over the univariate (1D) rival methods using a rice dataset, where four traditional traits (i.e. yield, 1000-grain weight, grain number and tiller number) as well as 1000 metabolomic traits were analyzed. The novelty of the method is the incorporation of the HAT methodology in the 2D BLUP GS model such that the computational efficiency has been dramatically increased by avoiding the conventional cross-validation. The results indicated that (1) the 2D BLUP-HAT GS analysis generally produces higher predictabilities for two traits than those achieved by the analysis of individual traits using 1D GS model, and (2) selected metabolites may be utilized as ancillary traits in the new 2D BLUP-HAT GS method to further boost the predictability of traditional traits, especially for agronomically important traits with low 1D predictabilities.

Extended application of genomic selection to screen multiomics data for prognostic signatures of prostate cancer.

Prognostic tests using expression profiles of several dozen genes help provide treatment choices for prostate cancer (PCa). However, these tests require improvement to meet the clinical need for resolving overtreatment, which continues to be a pervasive problem in PCa management. Genomic selection (GS) methodology, which utilizes whole-genome markers to predict agronomic traits, was adopted in this study for PCa prognosis. We leveraged The Cancer Genome Atlas (TCGA) database to evaluate the prediction performance of six GS methods and seven omics data combinations, which showed that the Best Linear Unbiased Prediction (BLUP) model outperformed the other methods regarding predictability and computational efficiency. Leveraging the BLUP-HAT method, an accelerated version of BLUP, we demonstrated that using expression data of a large number of disease-relevant genes and with an integration of other omics data (i.e. miRNAs) significantly increased outcome predictability when compared with panels consisting of a small number of genes. Finally, we developed a novel stepwise forward selection BLUP-HAT method to facilitate searching multiomics data for predictor variables with prognostic potential. The new method was applied to the TCGA data to derive mRNA and miRNA expression signatures for predicting relapse-free survival of PCa, which were validated in six independent cohorts. This is a transdisciplinary adoption of the highly efficient BLUP-HAT method and its derived algorithms to analyze multiomics data for PCa prognosis. The results demonstrated the efficacy and robustness of the new methodology in developing prognostic models in PCa, suggesting a potential utility in managing other types of cancer.

Tissue-specific expression of GhnsLTPs identified via GWAS sophisticatedly coordinates disease and insect resistance by regulating metabolic flux redirection in cotton.

Cotton (Gossypium hirsutum) is constantly attacked by pathogens and insects. The most efficient control strategy is to develop resistant varieties using broad-spectrum gene resources. Several resistance loci harboured by superior varieties have been identified through genome-wide association studies. However, the key genes and/or loci have not been functionally identified. In this study, we identified a locus significantly associated with Verticillium wilt (VW) resistance, and within a 145.5-kb linkage disequilibrium, two non-specific lipid transfer protein genes (named GhnsLTPsA10) were highly expressed under Verticillium pathogen stress. The expression of GhnsLTPsA10 significantly increased in roots upon Verticillium dahliae stress but significantly decreased in leaves under insect attack. Furthermore, GhnsLTPsA10 played antagonistic roles in positively regulating VW and Fusarium wilt resistance and negatively mediating aphid and bollworm resistance in transgenic Arabidopsis and silenced cotton. By combining transcriptomic, histological and physiological analyses, we determined that GhnsLTPsA10-mediated phenylpropanoid metabolism further affected the balance of the downstream metabolic flux of flavonoid and lignin biosynthesis. The divergent expression of GhnsLTPsA10 in roots and leaves coordinated resistance of cotton against fungal pathogens and insects via the redirection of metabolic flux. In addition, GhnsLTPsA10 contributed to reactive oxygen species accumulation. Therefore, in this study, we elucidated the novel function of GhnsLTP and the molecular association between disease resistance and insect resistance, balanced by GhnsLTPsA10. This broadens our knowledge of the biological function of GhnsLTPsA10 in crops and provides a useful locus for genetic improvement of cotton.

The polymorphism analysis and epitope predicted of Alphapapillomavirus 9 E6 in Sichuan, China.

BACKGROUND: The Alphapapillomavirus 9 (α-9 HPV) is a member of the Alphapapillomavirus genus and Papillomaviridae family. These viruses are almost all carcinogenic HPV, which is closely related to 75% of invasive cervical cancer worldwide, and has a high prevalence in Sichuan. The carcinogenic function is mainly realized by its E6 oncoprotein. METHODS: Cell samples were collected by cervical scraped for HPV detecting and typing. HPV-16, HPV-31, HPV-33, HPV-52, HPV-58 5 α-9 genus HPV subtype positive samples were selected, their E6 gene was sequenced and analyzed. The positive selection sites of HPV E6 genes were estimated by PAML 4.8 server. The secondary and tertiary structure of E6 protein were predicted by PSIPred and Swiss-model. The T-cell antigen epitopes of E6 protein were predicted by IEDB. RESULTS: α-9 HPV has a high prevalence in Sichuan, China. From 2012 to 2017, 18,067 cell cervical samples were collected, and 3135 were detected with α-9 HPV infection. Among which, 250 cases HPV-16 E6, 96 cases HPV-31 E6, 216 cases HPV-33 E6, 288 cases HPV-52 E6 and 405 cases HPV-58 E6 were successfully amplified, 17, 6, 6, 13, and 4 non-synonymous nucleotide mutations were respectively detected in HPV-16, 31, 33, 52, and 58 E6, 7 positive selection sites of α-9 HPV E6 were selected out (D32E of HPV-16 E6, K35N, K93N and R145I of HPV-33 E6, K93R of HPV-52 E6, K93N and R145K of HPV-58 E6). The structure and antigen epitopes of E6 protein with amino acid substitution differ from those of wild-type E6 protein, especially for the mutation located in the E6 positive selection site. CONCLUSIONS: HPV E6 nucleotide non-synonymous mutation in the positive selection site influence the protein structure and decrease the antigen epitopes affinity of the E6 protein overall, making it more difficult for the HPV-infected cells to be detected by the immune system, and enhancing the HPV adaptability to the environment. Mutations influence the validity of HPV clinical diagnostic probes, the polymorphism analysis of α-9 HPV E6 enrich the data of HR-risk HPV in Sichuan China, and the detection probes designed with the polymorphism data in mind can improve the efficiency of clinical detection; Mutations influence epitopes affinity, the association of E6 polymorphism and epitope affinity can improve the design of therapeutic vaccine with good immunity and high generality antigen epitope; The above study all provide a good theoretical basis for the prevention and treatment of HPV-related diseases.

Isolation and Genome Sequence of a Novel Phosphate-Solubilizing Rhizobacterium Bacillus altitudinis GQYP101 and Its Effects on Rhizosphere Microbial Community Structure and Functional Traits of Corn Seedling.

Bacillus altitudinis is a widely distributed soil bacterium that has various functional activities, including remediation of contaminated soil, degradation of herbicides, and enhancement of plant growth. B. altitudinis GQYP101 was isolated from the rhizosphere soil of Lycium barbarum L. and demonstrated potential as a plant growth-promoting bacterium. In this work, strain GQYP101 could solubilize phosphorus, and increased the stem diameter, maximum leaf area, and fresh weight of corn in a pot experiment. Nitrogen and phosphorus contents of corn seedlings (aerial part) increased by 100% and 47.9%, respectively, after application of strain GQYP101. Concurrently, nitrogen and phosphorus contents of corn root also increased, by 55.40% and 20.3%, respectively. Furthermore, rhizosphere soil nutrients were altered and the content of available phosphorus increased by 73.2% after application of strain GQYP101. The mechanism by which strain GQYP101 improved plant growth was further investigated by whole genome sequence analysis. Strain GQYP101 comprises a circular chromosome and a linear plasmid. Some key genes of strain GQYP101 were identified that were related to phosphate solubilization, alkaline phosphatase, chemotaxis, and motility. The findings of this study may provide a theoretical basis for strain GQYP101 to enhance crop yield as microbial fertilizer.

A large-scale genomic association analysis identifies a fragment in Dt11 chromosome conferring cotton Verticillium wilt resistance.

Verticillium wilt (VW) is a destructive disease that results in great losses in cotton yield and quality. Identifying genetic variation that enhances crop disease resistance is a primary objective in plant breeding. Here we reported a GWAS of cotton VW resistance in a natural-variation population, challenged by different pathogenicity stains and different environments, and found 382 SNPs significantly associated with VW resistance. The associated signal repeatedly peaked in chromosome Dt11 (68 798 494-69 212 808) containing 13 core elite alleles undescribed previously. The core SNPs can make the disease reaction type from susceptible to tolerant or resistant in accessions with alternate genotype compared to reference genotype. Of the genes associated with the Dt11 signal, 25 genes differentially expressed upon Verticillium dahliae stress, with 21 genes verified in VW resistance via gene knockdown and/or overexpression experiments. We firstly discovered that a gene cluster of L-type lectin-domain containing receptor kinase (GhLecRKs-V.9) played an important role in VW resistance. These results proved that the associated Dt11 region was a major genetic locus responsible for VW resistance. The frequency of the core elite alleles (FEA) in modern varieties was significantly higher than the early/middle varieties (12.55% vs 4.29%), indicating that the FEA increased during artificial selection breeding. The current developmental resistant cultivars, JND23 and JND24, had fixed these core elite alleles during breeding without yield penalty. These findings unprecedentedly provided genomic variations and promising alleles for promoting cotton VW resistance improvement.

The genetic variability, phylogeny and functional significance of E6, E7 and LCR in human papillomavirus type 52 isolates in Sichuan, China.

BACKGROUND: Variations in human papillomavirus (HPV) E6 and E7 have been shown to be closely related to the persistence of the virus and the occurrence and development of cervical cancer. Long control region (LCR) of HPV has been shown multiple functions on regulating viral transcription. In recent years, there have been reports on E6/E7/LCR of HPV-16 and HPV-58, but there are few studies on HPV-52, especially for LCR. In this study, we focused on gene polymorphism of the HPV-52 E6/E7/LCR sequences, assessed the effects of variations on the immune recognition of viral E6 and E7 antigens, predicted the effect of LCR variations on transcription factor binding sites and provided more basic date for further study of E6/E7/LCR in Chengdu, China. METHODS: LCR/E6/E7 of the HPV-52 were amplified and sequenced to do polymorphic and phylogenetic analysis. Sequences were aligned with the reference sequence by MEGA 7.0 to identify SNP. A neighbor-joining phylogenetic tree was constructed by MEGA 7.0, followed by the secondary structure prediction of the related proteins using PSIPRED 4.0. The selection pressure of E6 and E7 coding regions were estimated by Bayes empirical Bayes analysis of PAML 4.9. The HLA class-I and II binding peptides were predicted by the Immune Epitope Database server. The B cell epitopes were predicted by ABCpred server. Transcription factor binding sites in LCR were predicted by JASPAR database. RESULTS: 50 SNP sites (6 in E6, 10 in E7, 34 in LCR) were found. From the most variable to the least variable, the nucleotide variations were LCR > E7 > E6. Two deletions were found between the nucleotide sites 7387-7391 (TTATG) and 7698-7700 (CTT) in all samples. A deletion was found between the nucleotide sites 7287-7288 (TG) in 97.56% (40/41) of the samples. The combinations of all the SNP sites and deletions resulted in 12 unique sequences. As shown in the neighbor-joining phylogenetic tree, except for one belonging to sub-lineage C2, others sequences clustered into sub-lineage B2. No positive selection was observed in E6 and E7. 8 non-synonymous amino acid substitutions (including E3Q and K93R in the E6, and T37I, S52D, Y59D, H61Y, D64N and L99R in the E7) were potential affecting multiple putative epitopes for both CD4+ and CD8+ T-cells and B-cells. A7168G was the most variable site (100%) and the binding sites for transcription factor VAX1 in LCR. In addition, the prediction results showed that LCR had the high probability binding sites for transcription factors SOX9, FOS, RAX, HOXA5, VAX1 and SRY. CONCLUSION: This study provides basic data for understanding the relation among E6/E7/LCR mutations, lineages and carcinogenesis. Furthermore, it provides an insight into the intrinsic geographical relatedness and biological differences of the HPV-52 variants, and contributes to further research on the HPV-52 therapeutic vaccine development.

Genetic variability of human papillomavirus type 39 based on E6, E7 and L1 genes in Southwest China.

BACKGROUND: Human papillomavirus type 39 associated with genital intraepithelial neoplasia and invasive cancers, has a high prevalence in Southwest China. HPV E6, E7 are two main papillomavirus oncoproteins, closely relate to the function of HPV immortalization, cell transformation, and carcinogenesis. L1 is the major capsid protein, can reflect the replication status of the virus in cells and the progression of cervical lesions. The purpose of this study is to reveal the prevalence of HPV 39 and the genetic polymorphisms of HPV39 based on E6, E7 and L1 gene in southwest China. METHODS: Cell samples were collected by cervical scraped for HPV detecting and typing, and HPV39 positive samples were selected out. Important E6, E7 and L1 genes of HPV39 were sequenced and analyzed for the study of HPV39 genetic polymorphisms. Phylogenetic trees were constructed by Maximum-likelihood and Kimura 2-parameters methods in Molecular Evolutionary Genetics Analysis version 6.0. The selection pressures of E6, E7 and L1 genes were estimated by Datamonkey web server. The secondary and three-dimensional structure of HPV39 E6, E7 proteins were created by sopma server and SWISS-MODEL software. RESULTS: 344 HPV39 positive samples were selected from 5718 HPV positive cell samples. Among HPV39 E6-E7 sequences, 20 single nucleotide mutations were detected, including 10 non-synonymous and 10 synonymous mutations; 26 single nucleotide mutations were detected in HPV39 L1 sequences, including 7 non-synonymous and 19 synonymous mutations respectively. 11 novel variants of HPV39 E6-E7 (5 in E6 and 6 in E7) and 14 novel variants of HPV39 L1 were identified in this study. A-branch was the most frequent HPV39 lineage in southwest China during our investigation. Selective pressure analysis showed that codon sites 26, 87, 151 in E6 and 75, 180, 222, 272, 284, 346, 356 in L1 were positively selected sites, as well as codon sites 45, 138, 309, 381 were negative selection sites in L1 gene, E7 has neither positive selection sites nor negative selection sites. A certain degree of secondary and three-dimensional structure dislocation was existed due to the non-synonymous mutations. CONCLUSIONS: Amino acid substitution affected the secondary and three-dimensional structure of HPV39, and resulting in the differences of carcinogenic potential and biological functions as well as the immune response due to the antigen epitopes difference, the antigen epitopes with stronger adaptability in Southwest will be screened out based on the above research results for the later vaccine development. And gene polymorphism of HPV39 in Southwest China may improve the effectiveness of clinical test and vaccine design, specifically for women in Southwest China.

Accurate prediction of maize grain yield using its contributing genes for gene-based breeding.

Accurately predicting the phenotypes of complex traits is crucial to enhanced breeding in plants and livestock, and to enhanced medicine in humans. Here we reports the first study accurately predicting complex traits using their contributing genes, especially their number of favorable alleles (NFAs), genotypes and transcript expressions, with the grain yield of maize, Zea mays L. When the NFAs or genotypes of only 27 SNP/InDel-containing grain yield genes were used, a prediction accuracy of r = 0.52 or 0.49 was obtained. When the expressions of grain yield gene transcripts were used, a plateaued prediction accuracy of r = 0.84 was achieved. When the phenotypes predicted with two or three of the genic datasets were used for progeny selection, the selected lines were completely consistent with those selected by phenotypic selection. Therefore, the genes controlling complex traits enable accurately predicting their phenotypes, thus desirable for gene-based breeding in crop plants.

Acupuncture induces adenosine in fibroblasts through energy metabolism and promotes proliferation by activating MAPK signaling pathway via adenosine3 receptor.

Acupuncture has many advantages in the treatment of certain diseases as opposed to drug therapy. Besides, adenosine has been revealed to affect cellular progression including proliferation. Therefore, this study aimed at exploring the mechanism involving acupuncture stress and adenosine in fibroblast proliferation. The fibroblasts from fascia tissues of the acupoint area (Zusanli) were stimulated by different levels of stress, different concentrations of adenosine, and agonist or antagonist of A3 receptor (A3 R) to investigate the effect of stress stimulation, adenosine, and adenosine-A3 R inhibition on fibroblasts. Then, the fibroblasts were treated with stress stimulation of 200 kPa or/and mitogen-activated protein kinase (MAPK) blocker. We revealed that stress stimulation and the binding of adenosine and A3 R promoted fibroblast proliferation in the fascial tissue, increased the expression of immune-related factors, adenosine and A3 R, and activated the MAPK signaling pathway. MAPK signaling pathway also directly affected the expression of adenosine, A3 R, and immune-related factors. Stress stimulation and adenosine treatment upregulated A3 R expression, and then activated the MAPK signaling pathway, which could in turn upregulate expression of adenosine, A3 R and immune-related factors, and promote cell proliferation. Adenosine is shown to form a positive feedback loop with the MAPK signaling pathway. Collectively, stress stimulation in vitro induces the increase of adenosine in fibroblasts through the energy metabolism and activation of the MAPK signaling pathway through A3 R, ultimately promoting fibroblast proliferation.

Hybrid breeding of rice via genomic selection.

Hybrid breeding is the main strategy for improving productivity in many crops, especially in rice and maize. Genomic hybrid breeding is a technology that uses whole-genome markers to predict future hybrids. Predicted superior hybrids are then field evaluated and released as new hybrid cultivars after their superior performances are confirmed. This will increase the opportunity of selecting true superior hybrids with minimum costs. Here, we used genomic best linear unbiased prediction to perform hybrid performance prediction using an existing rice population of 1495 hybrids. Replicated 10-fold cross-validations showed that the prediction abilities on ten agronomic traits ranged from 0.35 to 0.92. Using the 1495 rice hybrids as a training sample, we predicted six agronomic traits of 100 hybrids derived from half diallel crosses involving 21 parents that are different from the parents of the hybrids in the training sample. The prediction abilities were relatively high, varying from 0.54 (yield) to 0.92 (grain length). We concluded that the current population of 1495 hybrids can be used to predict hybrids from seemingly unrelated parents. Eventually, we used this training population to predict all potential hybrids of cytoplasm male sterile lines from 3000 rice varieties from the 3K Rice Genome Project. Using a breeding index combining 10 traits, we identified the top and bottom 200 predicted hybrids. SNP genotypes of the training population and parameters estimated from this training population are available for general uses and further validation in genomic hybrid prediction of all potential hybrids generated from all varieties of rice.

Surface-imprinted ß-cyclodextrin-functionalized carbon nitride nanosheets for fluorometric determination of sterigmatomycin.

ß-Cyclodextrin-functionalized carbon nitride nanosheets were modified with a molecularly imprinted polymer to obtain a fluorescent probe of type MIP@ß-CD/CNNS which is shown to enable fluorometric determination of sterigmatocystin (STG). The material was characterized by transmission electron microscopy, infrared spectra, powder X-ray diffraction, X-ray photoelectron spectroscopy, and by absorption and emission spectra. The modified CNNSs have a good fluorescence quantum yield (13%), high sorption capacity for STG (86 mg·g-1), fast adsorption rate (25 min), and superior adsorption selectivity (with an imprint factor 2.56). When used as an optical probe for STG, the CNNSs act as the chromophore, while ß-CD and MIP act as the recognition groups. The blue fluorescence of MIP@ß-CD/CNNS (with excitation/emission maxima at 368/432 nm) is quenched by STG. Fluorescence drops linearly in the 0.15 to 3.1 µM STG concentration range. The lower detection limit is 74 nM. The method was successfully applied to the determination of STG in spiked wheat extract. Conceivably, this detection scheme based on a combination of ß-CD inclusion and molecular imprinting may be extended to the detection of various other organic compounds. Graphical abstractSchematic representation of the preparation of surface-imprinted ß-cyclodextrin-functionalized carbon nitride nanosheets. These are used, along with a molecularly imprinted polymer, for fluorometric determination of sterigmatomycin.

Complex molecular mechanisms underlying seedling salt tolerance in rice revealed by comparative transcriptome and metabolomic profiling.

To understand the physiological and molecular mechanisms underlying seedling salt tolerance in rice (Oryza sativa L.), the phenotypic, metabolic, and transcriptome responses of two related rice genotypes, IR64 and PL177, with contrasting salt tolerance were characterized under salt stress and salt+abscisic acid (ABA) conditions. PL177 showed significantly less salt damage, lower Na(+)/K(+) ratios in shoots, and Na(+) translocation from roots to shoots, attributed largely to better salt exclusion from its roots and salt compartmentation of its shoots. Exogenous ABA was able to enhance the salt tolerance of IR64 by selectively decreasing accumulation of Na(+) in its roots and increasing K(+) in its shoots. Salt stress induced general and organ-specific increases of many primary metabolites in both rice genotypes, with strong accumulation of several sugars plus proline in shoots and allantoin in roots. This was due primarily to ABA-mediated repression of genes for degradation of these metabolites under salt. In PL177, salt specifically up-regulated genes involved in several pathways underlying salt tolerance, including ABA-mediated cellular lipid and fatty acid metabolic processes and cytoplasmic transport, sequestration by vacuoles, detoxification and cell-wall remodeling in shoots, and oxidation-reduction reactions in roots. Combined genetic and transcriptomic evidence shortlisted relatively few candidate genes for improved salt tolerance in PL177.

Prediction models for bioavailability of Cu and Zn during composting: Insights into machine learning.

Bioavailability assessment of heavy metals in compost products is crucial for evaluating associated environmental risks. However, existing experimental methods are time-consuming and inefficient. The machine learning (ML) method has demonstrated excellent performance in predicting heavy metal fractions. In this study, based on the conventional physicochemical properties of 260 compost samples, including compost time, temperature, electrical conductivity (EC), pH, organic matter (OM), total phosphorus (TP), total nitrogen, and total heavy metal contents, back propagation neural network, gradient boosting regression, and random forest (RF) models were used to predict the dynamic changes in bioavailable fractions of Cu and Zn during composting. All three models could be used for effective prediction of the variation trend in bioavailable fractions of Cu and Zn; the RF model showed the best prediction performance, with the prediction level higher than that reported in related studies. Although the key factors affecting changes among fractions were different, OM, EC, and TP were important for the accurate prediction of bioavailable fractions of Cu and Zn. This study provides simple and efficient ML models for predicting bioavailable fractions of Cu and Zn during composting, and offers a rapid evaluation method for the safe application of compost products.