[Lignans from stems and leaves of Cephalotaxus fortunei (â ¡)].

The present study aimed to explore the chemical constituents from the stems and leaves of Cephalotaxus fortunei. Seven lignans were isolated from the 75% ethanol extract of C. fortunei by various chromatographic methods, including silica gel, ODS column chromatography, and HPLC. The structures of the isolated compounds were elucidated according to physicochemical properties and spectral data. Compound 1 is a new lignan named cephalignan A. The known compounds were identified as 8-hydroxy-conidendrine(2), isolariciresinol(3), leptolepisol D(4), diarctigenin(5), dihydrodehydrodiconiferyl alcohol 9'-O-ß-D-glucopyranoside(6), and dihydrodehydrodiconiferyl alcohol 4-O-ß-D-glucopyranoside(7). Compounds 2 and 5 were isolated from the Cephalotaxus plant for the first time.

Triterpene Derivatives from Garcinia oligantha and Their Anti-Cancer Activity.

Phytochemical investigations of leaves and twigs from Garcinia oligantha Merr. resulted in the isolation of five undescribed triterpene derivatives (1-5) and six known analogs (6-11). Their structures were determined based on extensive spectroscopic data and high-resolution mass spectra analyses. Compounds 1-11 were tested for their in vitro cytotoxicity against three human cancer cell lines (HeLa, HepG-2, and MCF-7). Compounds 1, 2, 8, and 11 exhibited broad and significant cytotoxicity against the tested cell lines with IC50 values ranging from 5.04 to 21.55 µM. Compounds 5 and 9 showed cytotoxicity against HeLa and MCF-7 with IC50 values ranging from 13.22 to 19.62 µM. The preliminary structure-activity relationship for the 11 isolated compounds is also discussed.

Molecular Mechanisms for Anti-aging of Low-Vacuum Cold Plasma Pretreatment in Caenorhabditis elegans.

Cold plasma pretreatment has the potential of anti-aging. However, its molecular mechanism is still not clear. Here, cold plasma pretreatment was firstly used to investigate the anti-aging effects of Caenorhabditis elegans using transcriptomic technique. It showed that the optimal parameters of discharge power, processing time, and working pressure for cold plasma pretreatment were separately 100 W, 15 s, and 135 Pa. The released 0.32 mJ/cm2 of the moderate apparent energy density was possibly beneficial to the strong positive interaction between plasma and C. elegans. The longest lifespan (13.67 ± 0.50 for 30 days) was obviously longer than the control (10.37 ± 0.46 for 23 days). Furthermore, compared with the control, frequencies of head thrashes with an increase of 26.01% and 37.31% and those of body bends with an increase of 33.37% and 34.51% on the fourth and eighth day, respectively, indicated movement behavior was improved. In addition, the variation of the enzyme activity of superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA) hinted that the cold plasma pretreatment contributed to the enhanced anti-aging effects in nematodes. Transcriptomics analysis revealed that cold plasma pretreatment resulted in specific gene expression. Anatomical structure morphogenesis, response to stress, regulation of biological quality, phosphate-containing compound metabolic process, and phosphorus metabolic process were the most enriched biological process for GO analysis. Cellular response to heat stress and HSF1-dependent transactivation were the two most enriched KEGG pathways. This work would provide the methodological basis using cold plasma pretreatment and the potential gene modification targets for anti-aging study.

Proteomic Analysis Reveals the Importance of Exudates on Sclerotial Development in Sclerotinia sclerotiorum.

Sclerotinia sclerotiorum is a ubiquitous necrotrophic pathogenic fungus causing significant losses in a broad range of plant species. Sclerotia formed by S. sclerotiorum play important roles in both the fungal life cycle and the disease development cycle. Sclerotial exudation during sclerotial development is a characteristic feature of this fungus. In this study, a proteome-level investigation of proteins present in sclerotial exudates was conducted by high-throughput LC-MS/MS analysis. A total of 258 proteins were identified, in which 193 were annotated by GO annotation and 54 were classified by KEGG analysis. Four proteins related to plant cell wall degradation were further validated by measuring the corresponding enzymatic activity of the sclerotial exudates and/or by assessing the gene expression during sclerotial development. Results indicated that the proteins identified in sclerotial exudates help in the development of sclerotia and contribute to host cell necrosis caused by S. sclerotiorum. Furthermore, we proposed that sclerotial exudates can degrade plant cell walls to release carbohydrates that provide nutrition for fungal growth and possibly facilitate fungal cell wall assembly in developing sclerotia. This study also provides new insights on the morphogenesis and pathogenicity of other sclerotia-forming fungi.

Identification of key genes for type 1 diabetes mellitus by network-based guilt by association.

OBJECTIVE This study aimed to propose a co-expression-network (CEN) based gene functional inference by extending the "Guilt by Association" (GBA) principle to predict candidate gene functions for type 1 diabetes mellitus (T1DM). METHODS Firstly, transcriptome data of T1DM were retrieved from the genomics data repository for differentially expressed gene (DEGs) analysis, and a weighted differential CEN was generated. The area under the receiver operating characteristics curve (AUC) was chosen to determine the performance metric for each Gene Ontology (GO) term. Differential expression analysis identified 325 DEGs in T1DM, and co-expression analysis generated a differential CEN of edge weight > 0.8. RESULTS A total of 282 GO annotations with DEGs > 20 remained for functional inference. By calculating the multifunctionality score of genes, gene function inference was performed to identify the optimal gene functions for T1DM based on the optimal ranking gene list. Considering an AUC > 0.7, six optimal gene functions for T1DM were identified, such as regulation of immune system process and receptor activity. CONCLUSIONS CEN-based gene functional inference by extending the GBA principle predicted 6 optimal gene functions for T1DM. The results may be potential paths for therapeutic or preventive treatments of T1DM.

Identification of key genes for type 1 diabetes mellitus by network-based guilt by association

SUMMARY OBJECTIVE This study aimed to propose a co-expression-network (CEN) based gene functional inference by extending the "Guilt by Association" (GBA) principle to predict candidate gene functions for type 1 diabetes mellitus (T1DM). METHODS Firstly, transcriptome data of T1DM were retrieved from the genomics data repository for differentially expressed gene (DEGs) analysis, and a weighted differential CEN was generated. The area under the receiver operating characteristics curve (AUC) was chosen to determine the performance metric for each Gene Ontology (GO) term. Differential expression analysis identified 325 DEGs in T1DM, and co-expression analysis generated a differential CEN of edge weight > 0.8. RESULTS A total of 282 GO annotations with DEGs > 20 remained for functional inference. By calculating the multifunctionality score of genes, gene function inference was performed to identify the optimal gene functions for T1DM based on the optimal ranking gene list. Considering an AUC > 0.7, six optimal gene functions for T1DM were identified, such as regulation of immune system process and receptor activity. CONCLUSIONS CEN-based gene functional inference by extending the GBA principle predicted 6 optimal gene functions for T1DM. The results may be potential paths for therapeutic or preventive treatments of T1DM.

RESUMO OBJETIVO O objetivo deste estudo é realizar uma inferência funcional genética baseada na rede de coexpressão (CEN), expandindo o escopo do princípio de "Culpa por Associação" (GBA - Guilt by Association) para prever as funções genéticas do diabetes mellitus tipo 1 (T1DM). MÉTODOS Primeiro, os dados transcritos do T1DM foram recuperados do repositório de dados genômicos para a análise dos genes diferenciais (DEGs), e foi gerada uma CEN diferencial ponderada. A área sob a curva ROC (AUC) foi escolhida para determinar a métrica de desempenho para cada termo de Ontologia Genética (GO). A análise da expressão diferencial identificou 325 DEGs no T1DM, e a análise de coexpressão gerou uma CEN diferencial com aresta de peso >0,8. RESULTADOS Um total de 282 anotações de GO com DEGs >20 foram mantidas para inferência funcional. Ao calcular a pontuação de multifuncionalidade dos genes, a inferência da função genética foi realizada para identificar as funções genéticas ideais para T1DM com base na lista de classificação genética ideal. Considerando um valor de AUC >0,7, foram identificadas seis funções genéticas ideais para a T1DM, tais como a regulação do processo imunológico e da atividade dos receptores. CONCLUSÕES A inferência funcional genética baseada em CEN, ao expandir o princípio de GBA, previu seis funções genéticas ideais para o T1DM. Os resultados podem ser caminhos potenciais para tratamentos terapêuticos ou preventivos do T1DM.

Mechanistic details of metal-free cyclization reaction of organophosphorus oxide with alkynes mediated by 2,6-lutidine and Tf2 O.

Theoretical investigations have elucidated the mechanism of metal-free electrophilic phosphinative cyclization of alkynes reaction reported by Miura and coworkers. Two competitive mechanisms I and II were explored without or with 2,6-lutidine. Both of I and II involve transformation of P(V) to P(III), electrophilic addition, ring opening and cyclization/cyclization, hydrogen-transfer, and oxidation. The rate-determining step of mechanism I and competitive less-step II is electrophilic [2 + 1] cycloaddition and electrophilic addition via single CP bond formation with activation barrier of 13.5 and 10.6 kcal/mol, respectively. Our calculation results suggested that the cumulative effect of the isomer of 2,6-lutidine and Tf2 O as well as TfO- affects the title reaction to some extent, and simultaneously activates key reaction sites and reverses the polarities of them via the formation of abundant noncovalent interactions to decrease activation barriers of TSs. In addition, the effects of two series substituents on reactivity of phosphine oxide were investigated. Therefore, our study will serve as useful guidance for more efficient metal-free synthesis of organophosphorus compounds mediated by pyridine reagents.

Identification and characterization of Colletotrichum destructivum causing anthracnose on sunflower.

Sunflower is one of the most economically important oil crops. Recently, sunflower anthracnose caused by Colletotrichum destructivum was reported and suggested to be a potential threat to the quality of oil and edible seeds derived from sunflower in the field and even on the ornamentals in the residential gardens. Colletotrichum destructivum, as the causal agent of sunflower anthracnose, has been rarely studied. In this study, the vegetative growth and sporulation of this fungal species were investigated by assessing the requirements of nutrition and other environmental conditions, such as temperature, ambient pH, and lightness regime. Additionally, the sensitivity of C. destructivum to several fungicides was assessed. The results will provide a baseline for better understanding of the biology and etiology of C. destructivum. This study will be the first reference for a sustainable management strategy according to the occurrence and prevalence of the sunflower anthracnose.

Prediction of seed gene function in progressive diabetic neuropathy by a network-based inference method.

Guilt by association (GBA) algorithm has been widely used to statistically predict gene functions, and network-based approach increases the confidence and veracity of identifying molecular signatures for diseases. This work proposed a network-based GBA method by integrating the GBA algorithm and network, to identify seed gene functions for progressive diabetic neuropathy (PDN). The inference of predicting seed gene functions comprised of three steps: i) Preparing gene lists and sets; ii) constructing a co-expression matrix (CEM) on gene lists by Spearman correlation coefficient (SCC) method and iii) predicting gene functions by GBA algorithm. Ultimately, seed gene functions were selected according to the area under the receiver operating characteristics curve (AUC) index. A total of 79 differentially expressed genes (DEGs) and 40 background gene ontology (GO) terms were regarded as gene lists and sets for the subsequent analyses, respectively. The predicted results obtained from the network-based GBA approach showed that 27.5% of all gene sets had a good classified performance with AUC >0.5. Most significantly, 3 gene sets with AUC >0.6 were denoted as seed gene functions for PDN, including binding, molecular function and regulation of the metabolic process. In summary, we predicted 3 seed gene functions for PDN compared with non-progressors utilizing network-based GBA algorithm. The findings provide insights to reveal pathological and molecular mechanism underlying PDN.

Formal [4 + 1] Annulation of α-Arylhydrazonoketones and Dimethylsulfoxonium Methylide: One-pot Synthesis of Substituted Pyrazoles and Dihydropyrazoles.

A formal [4 + 1] annulation of readily available α-arylhydrazonoketones and trimethylsulfoxonium iodide in the presence of cesium carbonate is described involving a sequential Corey-Chaykovsky reaction and intramolecular nucleophilic cyclization process. Substituted pyrazoles were obtained exclusively from the reactions of α-arylhydrazono-ß-oxo-amides and trimethylsulfoxonium iodide in moderate to good yields, whereas the reactions of α-arylhydrazono-ß-oxo-ketone/α-arylhydrazono- ß-oxo-ester afforded the corresponding dihydropyrazoles in good yields.