Selenated NHC-Pd(II) Pincer Complex Catalyzed, Temperature-Dependent Selective Hydroamination and Oxidative Amination of Olefins: Formation of Enamine Esters and ß-Amino Esters under Solvent-Free and Aerobic Conditions.

NHC-Pd(II) pincer catalyzed oxidative amination and hydroamination of olefins is developed under solvent-free aerobic conditions. Reaction offered a temperature-controlled synthesis of (Z)-enamine and ß-amino esters to provide easy access and remarkable functional group tolerance for a variety of enamines. The developed approach renders an opportunity of scalability and flexibility, and besides this, the produced enamines can be transformed into many N-containing heterocycles, underscoring its potential usage in synthetic and pharmaceutical chemistry. Moreover, it is the first report for coupling of aniline with styrene.

Ru-Catalyzed and Selenium-Directed Selective Formation of ortho- and Dialkenylated Selanes, Mixed Organoselenoethers, and Isoselenochromenes.

Herein, the Ru-catalyzed chemo- and regioselective formation of four novel organoselenium compounds is established. Mono- and dialkenylated selanes were formed by the Se-directed o-C-H activation of benzyl(phenyl)selanes with alkynes. Unprecedented debenzylative/dearylative hydroselenations of alkynes were performed by slightly varying the amount of catalyst and temperature. Catalyst-driven direct formation of novel isoselenochromenes is also recorded. Altogether, 45 new organoseleno compounds were synthesized in good amounts with varieties of alkynes and selanes. This is the first report of its kind to deal with the synthesis of novel, challenging, and unusual organoseleno compounds in one reaction.

Regulation of miR394 in Response to Fusarium oxysporum f. sp. cepae (FOC) Infection in Garlic (Allium sativum L).

MicroRNAs (miRNAs) are a class of post-transcriptional regulators that negatively regulate gene expression through target mRNA cleavage or translational inhibition and play important roles in plant development and stress response. In the present study, six conserved miRNAs from garlic (Allium sativum L.) were analyzed to identify differentially expressed miRNAs in response to Fusarium oxysporum f. sp. cepae (FOC) infection. Stem-loop RT-PCR revealed that miR394 is significantly induced in garlic seedlings post-treatment with FOC for 72 h. The induction of miR394 expression during FOC infection was restricted to the basal stem plate tissue, the primary site of infection. Garlic miR394 was also upregulated by exogenous application of jasmonic acid. Two putative targets of miR394 encoding F-box domain and cytochrome P450 (CYP450) family proteins were predicted and verified using 5' RLM-RACE (RNA ligase mediated rapid amplification of cDNA ends) assay. Quantitative RT-PCR showed that the transcript levels of the predicted targets were significantly reduced in garlic plants exposed to FOC. When garlic cultivars with variable sensitivity to FOC were exposed to the pathogen, an upregulation of miR394 and down regulation of the targets were observed in both varieties. However, the expression pattern was delayed in the resistant genotypes. These results suggest that miR394 functions in negative modulation of FOC resistance and the difference in timing and levels of expression in variable genotypes could be examined as markers for selection of FOC resistant garlic cultivars.

Development of Prediction Model and Experimental Validation in Predicting the Curcumin Content of Turmeric (Curcuma longa L.).

The drug yielding potential of turmeric (Curcuma longa L.) is largely due to the presence of phyto-constituent 'curcumin.' Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN) was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8) was the most suitable one with R2 value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site.