MFR-DTA: a multi-functional and robust model for predicting drug-target binding affinity and region.

MOTIVATION: Recently, deep learning has become the mainstream methodology for drug-target binding affinity prediction. However, two deficiencies of the existing methods restrict their practical applications. On the one hand, most existing methods ignore the individual information of sequence elements, resulting in poor sequence feature representations. On the other hand, without prior biological knowledge, the prediction of drug-target binding regions based on attention weights of a deep neural network could be difficult to verify, which may bring adverse interference to biological researchers. RESULTS: We propose a novel Multi-Functional and Robust Drug-Target binding Affinity prediction (MFR-DTA) method to address the above issues. Specifically, we design a new biological sequence feature extraction block, namely BioMLP, that assists the model in extracting individual features of sequence elements. Then, we propose a new Elem-feature fusion block to refine the extracted features. After that, we construct a Mix-Decoder block that extracts drug-target interaction information and predicts their binding regions simultaneously. Last, we evaluate MFR-DTA on two benchmarks consistently with the existing methods and propose a new dataset, sc-PDB, to better measure the accuracy of binding region prediction. We also visualize some samples to demonstrate the locations of their binding sites and the predicted multi-scale interaction regions. The proposed method achieves excellent performance on these datasets, demonstrating its merits and superiority over the state-of-the-art methods. AVAILABILITY AND IMPLEMENTATION: https://github.com/JU-HuaY/MFR.

2-Hydroxy-phytanoyl-CoA lyase (AtHPCL) is involved in phytol metabolism in Arabidopsis.

During chlorophyll degradation, large amounts of the isoprenoid alcohol phytol are released. The pathway of phytol catabolism has been studied in humans, because chlorophyll is part of the human diet, but little is known for plants. In humans, phytanoyl-CoA derived from phytol is degraded via α-oxidation by phytanoyl-CoA hydroxylase (PAHX) and 2-hydroxy-phytanoyl-CoA lyase (HPCL). Arabidopsis contains two sequences homologous to the human proteins AtPAHX and AtHPCL. Insertional mutants of Arabidopsis (pahx, hpcl) were grown under N deprivation to stimulate chlorophyll breakdown or supplemented with phytol to increase the endogenous amount of phytol. During N deprivation, chlorophyll, phytol, phytenal, upstream metabolites of phytol breakdown, and tocopherol and fatty acid phytyl esters, alternative phytol-derived lipids, accumulated in pahx and hpcl mutants, in line with the scenario that the mutations interfere with phytol degradation. AtHPCL was localized to the peroxisomes. Expression analysis of the AtHPCL sequence in the yeast Δpxp1 or Δmpo1 mutants followed by supplementation with 2-hydroxy-palmitic acid and enzyme assays of peroxisomal proteins from Col-0 and hpcl plants with 2-hydroxy-stearoyl-CoA revealed that AtHPCL harbors 2-hydroxy-acyl-CoA lyase activity. The α-dioxygenases αDOX1 and αDOX2 are involved in α-oxidation of fatty acids and could be involved in an alternative pathway of phytol degradation. However, phytol-related lipids in the αdox1, αdox2, or αdox1 αdox2 mutants were not altered compared with Col-0, indicating that αDOX1 and αDOX2 are not involved in phytol degradation. These results demonstrate that phytol degradation in Arabidopsis involves α-oxidation by AtPAHX and AtHPCL, but that it is independent of αDOX1/αDOX2.

Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation.

As an essential task in protein structure and function prediction, protein fold recognition has attracted increasing attention. The majority of the existing machine learning-based protein fold recognition approaches strongly rely on handcrafted features, which depict the characteristics of different protein folds; however, effective feature extraction methods still represent the bottleneck for further performance improvement of protein fold recognition. As a powerful feature extractor, deep convolutional neural network (DCNN) can automatically extract discriminative features for fold recognition without human intervention, which has demonstrated an impressive performance on protein fold recognition. Despite the encouraging progress, DCNN often acts as a black box, and as such, it is challenging for users to understand what really happens in DCNN and why it works well for protein fold recognition. In this study, we explore the intrinsic mechanism of DCNN and explain why it works for protein fold recognition using a visual explanation technique. More specifically, we first trained a VGGNet-based DCNN model, termed VGGNet-FE, which can extract fold-specific features from the predicted protein residue-residue contact map for protein fold recognition. Subsequently, based on the trained VGGNet-FE, we implemented a new contact-assisted predictor, termed VGGfold, for protein fold recognition; we then visualized what features were extracted by each of the convolutional layers in VGGNet-FE using a deconvolution technique. Furthermore, we visualized the high-level semantic information, termed fold-discriminative region, of a predicted contact map from the localization map obtained from the last convolutional layer of VGGNet-FE. It is visually confirmed that VGGNet-FE could effectively extract distinct fold-discriminative regions for different types of protein folds, thereby accounting for the improved performance of VGGfold for protein fold recognition. In summary, this study is of great significance for both understanding the working principle of DCNNs in protein fold recognition and exploring the relationship between the predicted protein contact map and protein tertiary structure. This proposed visualization method is flexible and applicable to address other DCNN-based bioinformatics and computational biology questions. The online web server of VGGfold is freely available at http://csbio.njust.edu.cn/bioinf/vggfold/.

SFPFusion: An Improved Vision Transformer Combining Super Feature Attention and Wavelet-Guided Pooling for Infrared and Visible Images Fusion.

The infrared and visible image fusion task aims to generate a single image that preserves complementary features and reduces redundant information from different modalities. Although convolutional neural networks (CNNs) can effectively extract local features and obtain better fusion performance, the size of the receptive field limits its feature extraction ability. Thus, the Transformer architecture has gradually become mainstream to extract global features. However, current Transformer-based fusion methods ignore the enhancement of details, which is important to image fusion tasks and other downstream vision tasks. To this end, a new super feature attention mechanism and the wavelet-guided pooling operation are applied to the fusion network to form a novel fusion network, termed SFPFusion. Specifically, super feature attention is able to establish long-range dependencies of images and to fully extract global features. The extracted global features are processed by wavelet-guided pooling to fully extract multi-scale base information and to enhance the detail features. With the powerful representation ability, only simple fusion strategies are utilized to achieve better fusion performance. The superiority of our method compared with other state-of-the-art methods is demonstrated in qualitative and quantitative experiments on multiple image fusion benchmarks.

Exonic Circular RNAs Are Involved in Arabidopsis Immune Response Against Bacterial and Fungal Pathogens and Function Synergistically with Corresponding Linear RNAs.

Circular RNAs (circRNAs) are a group of covalently closed RNAs, and their biological function is largely unknown. In this study, we focused on circRNAs that are generated from exon back-splicing (exonic circRNAs). The linear RNA counterparts encode functional proteins so that we can compare and investigate the relationship between circular and linear RNAs. We compared circRNA expression profiles between untreated and Pseudomonas syringae-infected Arabidopsis and identified and experimentally validated differentially expressed exonic circRNAs by multiple approaches. We found that exonic circRNAs are preferentially enriched in biological processes that associate with biotic and abiotic stress responses. We discovered that circR194 and circR4022 are involved in plant response against P. syringae infection, whereas circR11208 is involved in response against Botrytis cinerea infection. Intriguingly, our results indicate that these exonic circRNAs function synergistically with their corresponding linear RNAs. Furthermore, circR4022 and circR11208 also play substantial roles in Arabidopsis tolerance to salt stress. This study extends our understanding of the molecular functions of plant circRNAs.

Selectfluor-Promoted Intramolecular N-S Bond Formation of α-Carbamoyl Ketene Dithioacetals in the Presence of Water: Synthesis of Multifunctionalized Isothiazolones.

A practical and efficient protocol toward fully substituted isothiazolones through Selectfluor-mediated intramolecular oxidative annulation of α-carbamoyl ketene dithioacetals has been developed in the presence of H2O and metal-free conditions. Notably, the experimental results reveal that H2O was crucial to the formation of new N-S bonds and the elimination of alkyl group from the sulfur atom. This protocol provides readily prepared substrates and possesses good functional group tolerance, mild reaction conditions, and operational simplicity, which provides potential access to applications in the pharmaceutical chemistry.

Circulating exosomal microRNAs as emerging non-invasive clinical biomarkers in heart failure: Mega bio-roles of a nano bio-particle.

Exosomes are nano-sized extracellular vesicles containing a cell-specific biologically active cargo of proteins and genetic materials. Exosomes are constitutively released from almost all cell-types and affect neighboring or distant cells through a complex intercellular exchange of the genetic information and/or regulation of certain gene expressions that change the function and behavior of recipient cells. Those released into body fluids are the major mediators of intercellular communications. The success of the biological functions of exosomes is highly mediated by the effective transfer of microRNAs (miRs). Exosomes secreted by a damaged or diseased heart can exhibit alterations in the miRs' profile that may reflect the cellular origin and (patho)physiological state, as a "signature" or "fingerprint" of the donor cell. It has been shown that the transportation of cardiac-specific miRs in exosomes can be rapidly detected and measured, holding great potential as biomarkers in heart diseases. Currently, the search for new biomarkers of heart diseases remains a large and increasing enterprise. Notably, circulating exosomal miRs (Exo-miRs) have successfully gained huge interests for their diagnostic and prognostic potentials. The present review highlights circulating Exo-miRs explored for diagnosis/prognosis and outcome prediction in patients with heart failure (HF). To this end, we explain the feasibility of exosomes as clinical biomarkers, discuss the priority of circulating Exo-miRs over non-exosomal ones as a biomarker, and then outline reported circulating Exo-miRs having the biomarker function in HF patients, together with their mechanism of action. In conclusion, circulating Exo-miRs represent emerging diagnostic (Exo-miR-92b-5p, Exo-miR-146a, Exo-miR-181c, and Exo-miR-495) and prognostic (Exo-miR-192, Exo-miR-194, Exo-miR-34a, Exo-miR-425, Exo-miR-744) biomarkers for HF.

Osa-miR164a targets OsNAC60 and negatively regulates rice immunity against the blast fungus Magnaporthe oryzae.

Exploring the regulatory mechanism played by endogenous rice miRNAs in defense responses against the blast disease is of great significance in both resistant variety breeding and disease control management. We identified rice defense-related miRNAs by comparing rice miRNA expression patterns before and after Magnaporthe oryzae strain Guy11 infection. We discovered that osa-miR164a expression reduced upon Guy11 infection at both early and late stages, which was perfectly associated with the induced expression of its target gene, OsNAC60. OsNAC60 encodes a transcription factor, over-expression of which enhanced defense responses, such as increased programmed cell death, greater ion leakage, more reactive oxygen species accumulation and callose deposition, and upregulation of defense-related genes. By using transgenic rice over-expressing osa-miR164a, and a transposon insertion mutant of OsNAC60, we showed that when the miR164a/OsNAC60 regulatory module was dysfunctional, rice developed significant susceptibility to Guy11 infection. The co-expression of OsNAC60 and osa-miR164a abolished the OsNAC60 activity, but not its synonymous mutant. We further validated that this regulatory module is conserved in plant resistance to multiple plant diseases, such as the rice sheath blight, tomato late blight, and soybean root and stem rot diseases. Our results demonstrate that the miR164a/OsNAC60 regulatory module manipulates rice defense responses to M. oryzae infection. This discovery is of great potential for resistant variety breeding and disease control to a broad spectrum of pathogens in the future.

Magnaporthe oryzae Induces the Expression of a MicroRNA to Suppress the Immune Response in Rice.

MicroRNAs play crucial roles in plant responses to pathogen infections. The rice blast disease, caused by the fungus Magnaporthe oryzae, is the most important disease of rice (Oryza sativa). To explore the microRNA species that participate in rice immunity against the rice blast disease, we compared the expression of small RNAs between mock- and M. oryzae-treated rice. We found that infection by M. oryzae strain Guy11 specifically induced the expression of rice miR319 and, consequently, suppressed its target gene TEOSINTE BRANCHED/CYCLOIDEA/PROLIFERATING CELL FACTOR1 (OsTCP21), which encodes a transcription factor. Using transgenic rice that overexpresses miR319b (OE) or expresses OsTCP21-Res (which is resistant to miR319-mediated silencing), we found that OsTCP21 is a positive regulator of the rice defense response against the blast disease. When wild-type and miR319b-OE rice were infected by Guy11, multiple jasmonic acid (JA) synthetic and signaling components were suppressed, indicating that Guy11 suppresses JA signaling through inducing miR319. In particular, we found that LIPOXYGENASE2 (LOX2) and LOX5 were specifically suppressed by miR319 overexpression or by Guy11 infection. LOXs are the key enzymes of JA synthesis, which catalyze the conversion of α-linoleic acid to hydroperoxy-octadecadienoic acid. The application of α-linoleic acid rescued disease symptoms on the OsTCP21-Res rice but not wild-type rice, supporting our hypothesis that OsLOX2 and OsLOX5 are the key JA synthesis genes hijacked by Guy11 to subvert host immunity and facilitate pathogenicity. We propose that induced expression of OsLOX2/5 may improve resistance to the rice blast disease.

DNAPred: Accurate Identification of DNA-Binding Sites from Protein Sequence by Ensembled Hyperplane-Distance-Based Support Vector Machines.

Accurate identification of protein-DNA binding sites is significant for both understanding protein function and drug design. Machine-learning-based methods have been extensively used for the prediction of protein-DNA binding sites. However, the data imbalance problem, in which the number of nonbinding residues (negative-class samples) is far larger than that of binding residues (positive-class samples), seriously restricts the performance improvements of machine-learning-based predictors. In this work, we designed a two-stage imbalanced learning algorithm, called ensembled hyperplane-distance-based support vector machines (E-HDSVM), to improve the prediction performance of protein-DNA binding sites. The first stage of E-HDSVM designs a new iterative sampling algorithm, called hyperplane-distance-based under-sampling (HD-US), to extract multiple subsets from the original imbalanced data set, each of which is used to train a support vector machine (SVM). Unlike traditional sampling algorithms, HD-US selects samples by calculating the distances between the samples and the separating hyperplane of the SVM. The second stage of E-HDSVM proposes an enhanced AdaBoost (EAdaBoost) algorithm to ensemble multiple trained SVMs. As an enhanced version of the original AdaBoost algorithm, EAdaBoost overcomes the overfitting problem. Stringent cross-validation and independent tests on benchmark data sets demonstrated the superiority of E-HDSVM over several popular imbalanced learning algorithms. Based on the proposed E-HDSVM algorithm, we further implemented a sequence-based protein-DNA binding site predictor, called DNAPred, which is freely available at http://csbio.njust.edu.cn/bioinf/dnapred/ for academic use. The computational experimental results showed that our predictor achieved an average overall accuracy of 91.7% and a Mathew's correlation coefficient of 0.395 on five benchmark data sets and outperformed several state-of-the-art sequence-based protein-DNA binding site predictors.

Histogram-Based CRC for 3D-Aided Pose-Invariant Face Recognition.

Traditional Collaborative Representation-based Classification algorithms for face recognition (CRC) usually suffer from data uncertainty, especially if it includes various poses and illuminations. To address this issue, in this paper, we design a new CRC method using histogram statistical measurement (H-CRC) combined with a 3D morphable model (3DMM) for pose-invariant face classification. First, we fit a 3DMM to raw images in the dictionary to reconstruct the 3D shapes and textures. The fitting results are used to render numerous virtual samples of 2D images that are frontalized from arbitrary poses. In contrast to other distance-based evaluation algorithms for collaborative (or sparse) representation-based methods, the histogram information of all the generated 2D face images is subsequently exploited. Second, we use a histogram-based metric learning to evaluate the most similar neighbours of the test sample, which aims to obtain ideal result for pose-invariant face recognition using the designed histogram-based 3DMM model and online pruning strategy, forming a unified 3D-aided CRC framework. The proposed method achieves desirable classification results that are conducted on a set of well-known face databases, including ORL, Georgia Tech, FERET, FRGC, PIE and LFW.

Changes in unfrozen water content and dielectric properties during pulse vacuum osmotic dehydration to improve microwave freeze-drying characteristics of Chinese yam.

BACKGROUND: As a pretreatment before drying, the purpose of osmotic dehydration (OD) is to reduce the initial water content of samples and shorten the drying time. When OD is combined with pulse vacuum, the mass transfer is enhanced. Furthermore, the properties of materials, which affect the absorption and dissipation of microwaves, can be changed by OD. In this work, pulsed vacuum osmotic dehydration (PVOD) with sucrose solution was adopted before microwave freeze-drying (MFD). The effects of PVOD on the drying characteristics and quality of dried products were studied. RESULTS: Results showed that the unfrozen water content was increased by PVOD, which made the dielectric constant and loss factor of Chinese yam larger than that of untreated samples, and the difference amplified with the increasing temperature. Thus, the shortened drying time (up to 38.5%) and increased average drying rate (up to 16.8%) were achieved by MFD combined with PVOD. While in traditional freeze-drying, PVOD resulted in slightly shortened drying time but decreased drying rate. The mechanism of PVOD on improving drying rate of MFD was analyzed from the perspective of unfrozen water content and dielectric properties. Furthermore, the quality assessments indicated that PVOD treatment retained a better color and improved the total phenolic content of dried yams compared to untreated and dried samples. CONCLUSION: PVOD using sucrose solution was an effective method to change the characteristics of yam, enhancing the MFD rate and improving the product qualities. © 2019 Society of Chemical Industry.

Study on association between ERCC5 single nucleotide polymorphism and susceptibility to esophageal cancer.

PURPOSE: DNA repair genes play important roles in the genesis of esophageal cancer, and their functional single nucleotide polymorphism (SNP) loci may affect the susceptibility to esophageal cancer through changing the capability of DNA damage repair. METHODS: A total of 557 patients with esophageal squamous cell carcinoma and 1503 age- and gender-matched healthy people were selected in this study. The hospital-based case-control method and the candidate gene and functional locus-based SNP selection strategy were used to screen three functional SNPs, loci on excision repair cross complement 5 (ERCC5): rs2296147, rs873601 and rs2094258. Genotyping was performed using Taqman method. A logistic regression model was used to analyze the relationship between the selected loci and the risk of esophageal cancer. RESULTS: rs2296147 reduced the risk of esophageal cancer (CC vs TT: OR=0.79, 95% CI=0.64-0.97, p=0.027; additive model: OR=0.80, 95% CI=0.68-0.94, p=0.007). The results of stratified analysis showed that rs2296147 could reduce the susceptibility to esophageal cancer in women, non-smokers, drinkers and non-drinkers. No correlation between rs873601 and rs2094258 and susceptibility to esophageal cancer was found. However, the combined effect analysis showed that rs2296147, rs873601 and rs2094258 could increase the risk of esophageal cancer (ptrend=0.006). CONCLUSION: The results of this case-control study showed that the polymorphic locus on ERCC5, rs2296147, could reduce the risk of esophageal cancer, which will help further understand the pathogenesis of esophageal cancer.

Reduction Responsive Self-Assembled Nanoparticles Based on Disulfide-Linked Drug-Drug Conjugate with High Drug Loading and Antitumor Efficacy.

Most anticancer drugs are poorly soluble and nonspecific, which restricts their clinical application. Drug conjugates, as a prodrug strategy, provide the possibility to overcome these shortcomings, especially combined with nanotechnology. Drug conjugate nanoparticles possess the advantages of high drug loading capacity and passive tumor targeting ability. Here, we prepared doxorubicin drug-drug conjugate nanoparticles (DOX-SS-DOX NPs) based on disulfide-linked doxorubicin drug-drug conjugate (DOX-SS-DOX). Dynamic light scattering (DLS) and transmission electron microscope (TEM) characterization indicated that DOX-SS-DOX NPs were spherical with a uniform size distribution around 89 nm. DLS and in vitro release experiment revealed that DOX-SS-DOX NPs possessed reduction responsive activity. In vitro cellular uptake studies reflected that DOX-SS-DOX NPs could increase the uptake level substantially compared with DOX liposomes. Endocytosis mechanism assay demonstrated that DOX-SS-DOX NPs internalized into cells through a clathrin-mediated endocytosis pathway in an energy-dependent manner. In this manner, the amidase in lysosomes could break the amide bond to release free DOX, which would be helpful to antitumor activity. The in vitro cytotoxicity of DOX-SS-DOX NPs was a bit weaker than that of DOX liposomes, which might be the result of the slow cleavage of the disulfide bridge; but the antitumor efficacy of DOX-SS-DOX NPs evaluated in MCF-7 bearing mice was demonstrated to be higher than that of DOX liposomes. This might be because of the long lasting effect resulting from the slow cleavage of the disulfide bond. In summary, DOX-SS-DOX NPs, prepared nearly totally with drug, provide a good strategy for cancer therapy.

[The integrity study on PEG-PCL micelles transcellular transported across MDCK epithelial cell monolayer using FRET technology].

The integrity of poly(ethylene glycol)-co-poly(ε-caprolactone) (PEG-PCL) micelles transcellular transported across madin-darby canine kidney(MDCK) epithelial cells was investigated. Fluorescein isothiocyanate isomer I(FITC) was conjugated to PEG-PCL and the product PEG-PCL-FITC was identified by fluorescence spectra. Two micelles were prepared using the thin-film hydration method: 3,3'-dioctadecyloxacarbocyanine perchlorate (DiO) and 1,1'-dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine perchlorate (DiI) co-loaded PEG-PCL micelles (DiO-DiI-M), DiI loaded and PEG-PCL-FITC contained micelles(FITC-DiI-M). The size of the micelles was characterized by dynamic light scattering analysis using a Malvern Zetasizer Nano ZS and it turned out that the particle sizes of both micelles were about 30 nm with identical polydispersity index(PDI). The stability of the micelles in phosphate buffer saline(PBS) was monitored using fluorescence spectra and both micelles were stable within 4 h in PBS. The integrity of PEG-PCL micelles in the transcellular process across MDCK epithelial cell monolayer at 1 and 4 h was investigated using laser confocal scanning microscope and Förster resonance energy transfer(FRET) technology. The Person's coefficient and FRET efficiency of both Transwell layer and Receive layer were recorded. The results show that the FRET efficiency and Person's coefficient of the Receive layer was consistent with that of Transwell layer for both the micelles at 1 h, but decreased at 4 h and FITC-DiI-M decreased more significantly than Di O-DiI-M. The results indicated that the micelles could transport across the MDCK monolayer intactly at 1 h but some of them were disassembled during the 4 h transportation process.

Rough set approach to incomplete multiscale information system.

Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments.

Enhancing char formation of flame retardant epoxy composites: Onigiri-like ZIF-67 modification with carboxymethyl ß-cyclodextrin crosslinking.

To enhance char formation of flame retardant epoxy (EP) composites, carboxymethyl ß-cyclodextrin (CM-ß-CD) is employed as an etchant for or ZIF-67 derivatives. In the early stage, etching plays a dominant role. The mismatch in size between CM-ß-CD opening and ZIF-67 pore leads to the stacking of carboxyl cobalt complexes on the shell. When the reaction time is prolonged, crosslinking occurs between carboxyl and hydroxyl groups. Crosslinked CM-ß-CD weakens and eventually stops the etching process. Triethyl phosphate (TEP), an additive to improve flame retardancy, is also absorbed on the shell in this one-pot synthesis. Herin, the synthesis of metal-organic framework (MOF) derivatives can impart multiple functions to MOF. This novel nanohybrid significantly improved flame retardancy of EP composites with only 2.0 wt% loading. The peak heat release rate (pHRR) and total smoke production (TSP) were reduced by 54.8 and 46.9%, respectively. The integrated multi-element system resulted in an expanded and reinforced char layer. This study proposes a simple and precise method for controlling the structure of MOF-carbohydrate hybrids through competition between chemical reactions.

Dual function of carboxymethyl cellulose scaffold: A one-stone-two-birds strategy to prepare double-layer hollow ZIF-67 derivates for flame retardant epoxy composites.

Aluminum hypophosphite (AHP) has been used as a flame retardant for a long time. Previous studies about AHP employed in flame retardant materials mostly focus on coating, modification, and complex system. It is valuable to explore simple experimental steps to prepare nano hybrids with AHP and metal-organic frameworks (MOFs). We found acidic substances could etch zeolitic imidazolate framework-67 (ZIF-67) to obtain MOF derivatives. Unfortunately, AHP and ZIF-67 could not directly form a hybrid. Therefore, carboxymethylcellulose (CMC) is introduced as a dual function layer (buffer and support). The CMC resists the complete conversion of ZIF-67 etched by phosphoric acid to amorphous cobalt phosphate hydrate (ACP). Meanwhile, CMC containing hydroxyl groups combines with AHP through electrostatic interaction and coordination bonds. A double-layer hollow MOF derivative is synthesized through this one-stone-two-birds strategy. Due to multiple flame retardant elements and unique nanostructure, this MOF derivative endows epoxy (EP) resin with excellent flame retardancy. With 2.0 wt% addition, the peak heat release rate (pHRR) and total heat release (THR) of EP/AHP/ACP@CMC are decreased by 47.8 and 21.0 %, respectively. This study proposes a novel scheme that converts AHP into MOF derivatives as high-performance FRs.

Efficacy and toxic action of the natural product natamycin against Sclerotinia sclerotiorum.

BACKGROUND: Sclerotinia stem rot caused by Sclerotinia sclerotiorum seriously endangers oilseed rape production worldwide, and the occurrence of fungicide-resistant mutants of S. sclerotiorum leads to control decline. Thus, it is critical to explore new green substitutes with different action mechanisms and high antifungal activity. Herein, the activity and the action mechanism of natamycin against S. sclerotiorum were evaluated. RESULTS: Natamycin showed potent inhibition on the mycelial growth of S. sclerotiorum, and half-maximal effective concentration (EC50 ) values against 103 S. sclerotiorum strains ranged from 0.53 to 4.04 µg/mL (mean 1.44 µg/mL). Natamycin also exhibited high efficacy against both carbendazim- and dimethachlone-resistant strains of S. sclerotiorum on detached oilseed rape leaves. No cross-resistance was detected between natamycin and carbendazim. Natamycin markedly disrupted hyphal form, sclerotia formation, integrity of the cell membrane, and reduced the content of oxalic acid and ergosterol, whereas it increased the reactive oxygen species (ROS) and malondialdehyde content. Interestingly, exogenous addition of ergosterol could reduce the inhibition of natamycin against S. sclerotiorum. Importantly, natamycin significantly inhibited expression of the Cyp51 gene, which is contrary to results for the triazole fungicide flusilazole, indicating a different action mechanism from triazole fungicides. CONCLUSION: Natamycin is a promising effective candidate for the resistance management of S. sclerotiorum. © 2023 Society of Chemical Industry.