Bacillus velezensis SYL-3 suppresses Alternaria alternata and tobacco mosaic virus infecting Nicotiana tabacum by regulating the phyllosphere microbial community

The occurrence of plant diseases is closely associated with the imbalance of plant tissue microecological environment. The regulation of the phyllosphere microbial communities has become a new and alternative approach to the biological control of foliar diseases. In this study, Bacillus velezensis SYL-3 isolated from Luzhou exhibited an effective inhibitory effect against Alternaria alternata and tobacco mosaic virus (TMV). The analysis of phyllosphere microbiome by PacBio sequencing indicated that SYL-3 treatment significantly altered fungal and bacterial communities on the leaves of Nicotiana tabacum plants and reduced the disease index caused by A. alternata and TMV. Specifically, the abundance of P. seudomo, Sphingomonas, Massilia, and Cladosporium in the SYL-3 treatment group increased by 19.00, 9.49, 3.34, and 12.29%, respectively, while the abundances of Pantoea, Enterobacter, Sampaiozyma, and Rachicladosporium were reduced. Moreover, the abundance of beneficial bacteria, such as Pseudomonas and Sphingomonas, was negatively correlated with the disease indexes of A. alternata and TMV. The PICRUSt data also predicted the composition of functional genes, with significant differences being apparent between SYL-3 and the control treatment group. Further functional analysis of the microbiome also showed that SYL-3 may induce host disease resistance by motivating host defense-related pathways. These results collectively indicate that SYL-3 may suppress disease progression caused by A. alternata or TMV by improving the microbial community composition on tobacco leaves

Transcriptomic and functional analyses reveal the molecular mechanisms underlying Fe-mediated tobacco resistance to potato virus Y infection

Potato virus Y (PVY) mainly infects Solanaceous crops, resulting in considerable losses in the yield and quality. Iron (Fe) is involved in various biological processes in plants, but its roles in resistance to PVY infection has not been reported. In this study, foliar application of Fe could effectively inhibit early infection of PVY, and a full-length transcriptome and Illumina RNA sequencing was performed to investigate its modes of action in PVY-infected Nicotiana tabacum. The results showed that 18,074 alternative splicing variants, 3,654 fusion transcripts, 3,086 long non-coding RNAs and 14,403 differentially expressed genes (DEGs) were identified. Specifically, Fe application down-regulated the expression levels of the DEGs related to phospholipid hydrolysis, phospholipid signal, cell wall biosynthesis, transcription factors (TFs) and photosystem I composition, while those involved with photosynthetic electron transport chain (PETC) were up-regulated at 1 day post inoculation (dpi). At 3 dpi, these DEGs related to photosystem II composition, PETC, molecular chaperones, protein degradation and some TFs were up-regulated, while those associated with light-harvesting, phospholipid hydrolysis, cell wall biosynthesis were down-regulated. At 9 dpi, Fe application had little effects on resistance to PVY infection and transcript profiles. Functional analysis of these potentially critical DEGs was thereafter performed using virus-induced gene silencing approaches and the results showed that NbCat-6A positively regulates PVY infection, while the reduced expressions of NbWRKY26, NbnsLTP, NbFAD3 and NbHSP90 significantly promote PVY infection in N. benthamiana. Our results elucidated the regulatory network of Fe-mediated resistance to PVY infection in plants, and the functional candidate genes also provide important theoretical bases to further improve host resistance against PVY infection

Armeniacae semen amarum: a review on its botany, phytochemistry, pharmacology, clinical application, toxicology and pharmacokinetics

Armeniacae semen amarum—seeds of Prunus armeniaca L. (Rosaceae) (ASA), also known as Kuxingren in Chinese, is a traditional Chinese herbal drug commonly used for lung disease and intestinal disorders. It has long been used to treat coughs and asthma, as well as to lubricate the colon and reduce constipation. ASA refers to the dried ripe seed of diverse species of Rosaceae and contains a variety of phytochemical components, including glycosides, organic acids, amino acids, flavonoids, terpenes, phytosterols, phenylpropanoids, and other components. Extensive data shows that ASA exhibits various pharmacological activities, such as anticancer activity, anti-oxidation, antimicrobial activity, anti-inflammation, protection of cardiovascular, neural, respiratory and digestive systems, antidiabetic effects, and protection of the liver and kidney, and other activities. In clinical practice, ASA can be used as a single drug or in combination with other traditional Chinese medicines, forming ASA-containing formulas, to treat various afflictions. However, it is important to consider the potential adverse reactions and pharmacokinetic properties of ASA during its clinical use. Overall, with various bioactive components, diversified pharmacological actions and potent efficacies, ASA is a promising drug that merits in-depth study on its functional mechanisms to facilitate its clinical application

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

PURPOSE This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism. METHODS This study involved 1017 subjects who underwent DAT PET imaging ([11C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning. RESULTS The proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP. CONCLUSION This study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis

Differential diagnosis of parkinsonism based on deep metabolic imaging indices.

The clinical presentations of early idiopathic Parkinson's disease (PD) substantially overlap with those of atypical parkinsonian syndromes like multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). This study aimed to develop metabolic imaging indices based on deep learning to support the differential diagnosis of these conditions. Methods: A benchmark Huashan parkinsonian PET imaging (HPPI, China) database including 1275 parkinsonian patients and 863 non-parkinsonian subjects with 18F-FDG PET images was established to support artificial intelligence development. A 3D deep convolutional neural network was developed to extract deep metabolic imaging (DMI) indices, which was blindly evaluated in an independent cohort with longitudinal follow-up from the HPPI, and an external German cohort of 90 parkinsonian patients with different imaging acquisition protocols. Results: The proposed DMI indices had less ambiguity space in the differential diagnosis. They achieved sensitivities of 98.1%, 88.5%, and 84.5%, and specificities of 90.0%, 99.2%, and 97.8% for the diagnosis of PD, MSA, and PSP in the blind test cohort. In the German cohort, They resulted in sensitivities of 94.1%, 82.4%, 82.1%, and specificities of 84.0%, 99.9%, 94.1% respectively. Employing the PET scans independently achieved comparable performance to the integration of demographic and clinical information into the DMI indices. Conclusion: The DMI indices developed on the HPPI database show potential to provide an early and accurate differential diagnosis for parkinsonism and is robust when dealing with discrepancies between populations and imaging acquisitions

The activity and selectivity of catalytic peroxide oxidation of chlorophenols over Cu-Al hydrotalcite/clay composite

Liquid phase catalytic oxidation of chlorophenols (CPs) was carried out over Cu-Al hydrotalcite/clay composite at ambient temperature and pressure using hydrogen peroxide as oxidant. The results showed that the catalyst had high catalytic activity, with complete oxidation of 4-CP within 40 min at 40 degrees C. The content and position of chlorine on the aromatic ring had significantly different effects on the oxidation rate of CPs, with the rate sequence of phenol > monochlorophenol (MCP) > dichlorophenol (DCP) > trichlorophenol (TCP), 3-CP > 2-CP > 4-CP. and 3,5-DCP > 3,4-DCP > 2,5-DCP > 2,4-DCP > 2,6-DCP. This was ascribed to the interactions among sigma-electron withdrawing conductive effect, pi-electron donating conjugative effect, and steric hindrance effect of chlorine. It was evidenced that the catalytic peroxide oxidation of CPs in the first step was selective and rate-limiting, where chlorinated 1,4-benzoquinones formed. (C) 2011 Elsevier Inc. All rights reserved.Liquid phase catalytic oxidation of chlorophenols (CPs) was carried out over Cu-Al hydrotalcite/clay composite at ambient temperature and pressure using hydrogen peroxide as oxidant. The results showed that the catalyst had high catalytic activity, with complete oxidation of 4-CP within 40 min at 40 degrees C. The content and position of chlorine on the aromatic ring had significantly different effects on the oxidation rate of CPs, with the rate sequence of phenol > monochlorophenol (MCP) > dichlorophenol (DCP) > trichlorophenol (TCP), 3-CP > 2-CP > 4-CP. and 3,5-DCP > 3,4-DCP > 2,5-DCP > 2,4-DCP > 2,6-DCP. This was ascribed to the interactions among sigma-electron withdrawing conductive effect, pi-electron donating conjugative effect, and steric hindrance effect of chlorine. It was evidenced that the catalytic peroxide oxidation of CPs in the first step was selective and rate-limiting, where chlorinated 1,4-benzoquinones formed. (C) 2011 Elsevier Inc. All rights reserved

The Flavonoid Quercetin Ameliorates Liver Inflammation and Fibrosis by Regulating Hepatic Macrophages Activation and Polarization in Mice

At present, there are no effective antifibrotic drugs for patients with chronic liver disease; hence, the development of antifibrotic therapies is urgently needed. Here, we performed an experimental and translational study to investigate the potential and underlying mechanism of quercetin treatment in liver fibrosis, mainly focusing on the impact of quercetin on macrophages activation and polarization. BALB/c mice were induced liver fibrosis by carbon tetrachloride (CCl4) for 8 weeks and concomitantly treated with quercetin (50 mg/kg) or vehicle by daily gavage. Liver inflammation, fibrosis, and hepatic stellate cells (HSCs) activation were examined. Moreover, massive macrophages accumulation, M1 macrophages and their related markers, such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, and monocyte chemotactic protein-1 (MCP-1) in livers were analyzed. In vitro, we used Raw 264.7 cells to examine the effect of quercetin on M1-polarized macrophages activation. Our results showed that quercetin dramatically ameliorated liver inflammation, fibrosis, and inhibited HSCs activation. These results were attributed to the reductive recruitment of macrophages (F4/80+ and CD68+) into the liver in quercetin-treated fibrotic mice confirmed by immunostaining and expression levels of marker molecules. Importantly, quercetin strongly inhibited M1 polarization and M1-related inflammatory cytokines in fibrotic livers when compared with vehicle-treated mice. In vitro, studies further revealed that quercetin efficiently inhibited macrophages activation and M1 polarization, as well as decreased the mRNA expression of M1 macrophage markers such as TNF-α, IL-1β, IL-6, and nitric oxide synthase 2. Mechanistically, the inhibition of M1 macrophages by quercetin was associated with the decreased levels of Notch1 expression on macrophages both in vivo and in vitro. Taken together, our data indicated that quercetin attenuated CCl4-induced liver inflammation and fibrosis in mice through inhibiting macrophages infiltration and modulating M1 macrophages polarization via targeting Notch1 pathway. Hence, quercetin holds promise as potential therapeutic agent for human fibrotic liver disease

Candidate Genes Involved in Tolerance to Fenoxaprop-P-Ethyl in Rice Induced by Isoxadifen-Ethyl Hydrolysate

The metabolic resistance of plants to herbicides is similar to the herbicide metabolism process accelerated by safeners. The tolerance to fenoxaprop-P-ethyl (FE) is distinct among different varieties of rice in which phytotoxicity forms easily, resulting in the restricted use of FE in paddy. Safener effectively resolves this issue. This study showed that rice 9311 and Meixiangzhan No. 2 (MXZ) had different tolerance mechanisms to FE. Isoxadifen-ethyl hydrolysate (IH) alleviated FE the inhibition of rice growth. Transcriptome sequencing revealed numerous differentially expressed genes (DEGs) between the two varieties. A total of 31 metabolic enzyme genes related to herbicide detoxification were screened by analyzing the DEGs in different rice varieties or treatments. The results of the quantitative reverse transcription polymerase chain reaction indicated that 12 genes were potential metabolic genes resistant to FE in rice. Additionally, the enhanced expression of GSTU6, DIMBOA UGT BX8, and ABCG39 was confirmed to be induced by safener. Taken together, our results demonstrated that the induced expression of these three genes might be crucial for resistance to herbicide phytotoxicity in crops. These results may help us to understand herbicide metabolism in crops and to develop novel strategies for the safe use of herbicides