Honey is a natural food item produced by honey bees. Ancient civilizations considered honey as a God gifted prestigious product. Therefore, a huge literature is available regarding honey importance in almost all religions. Physically, honey is a viscous and jelly material having no specific color. Chemically, honey is a complex blend of many organic and inorganic compounds such as sugars, proteins, organic acids, pigments, minerals, and many other elements. Honey use as a therapeutic agent is as old as human civilization itself. Prior to the appearance of present day drugs, honey was conventionally used for treating many diseases. At this instant, the modern research has proven the medicinal importance of honey. It has broad spectrum anti-biotic, anti-viral and anti-fungal activities. Honey prevents and kills microbes through different mechanism such as elevated pH and enzyme activities. Till now, no synthetic compound that works as anti-bacterial, anti-viral and anti-fungal drugs has been reported in honey yet it works against bacteria, viruses and fungi while no anti-protozoal activity has been reported. Potent anti-oxidant, anti-inflammatory and anti-cancerous activities of honey have been reported. Honey is not only significant as anti-inflammatory drug that relieve inflammation but also protect liver by degenerative effects of synthetic anti-inflammatory drugs. This article reviews physico-chemical properties, traditional use of honey as medicine and mechanism of action of honey in the light of modern scientific medicinal knowledge.

AbstractIn this paper, we introduce the notion of Einstein aggregation operators, such as the interval-valued Pythagorean fuzzy Einstein weighted averaging aggregation operator and the interval-valued Pythagorean fuzzy Einstein ordered weighted averaging aggregation operator. We also discuss some desirable properties, such as idempotency, boundedness, commutativity, and monotonicity. The main advantage of using the proposed operators is that these operators give a more complete view of the problem to the decision makers. These operators provide more accurate and precise results as compared the existing method. Finally, we apply these operators to deal with multiple-attribute group decision making under interval-valued Pythagorean fuzzy information. For this, we construct an algorithm for multiple-attribute group decision making. Lastly, we also construct a numerical example for multiple-attribute group decision making.

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Protein-protein interaction (PPI) network maintains proper function of all organisms. Simple high-throughput technologies are desperately needed to delineate the landscape of PPI networks. While recent state-of-the-art yeast two-hybrid (Y2H) systems improved screening efficiency, either individual colony isolation, library preparation arrays, gene barcoding or massive sequencing are still required. Here, we developed a recombination-based ‘library vs library’ Y2H system (RLL-Y2H), by which multi-library screening can be accomplished in a single pool without any individual treatment. This system is based on the phiC31 integrase-mediated integration between bait and prey plasmids. The integrated fragments were digested by MmeI and subjected to deep sequencing to decode the interaction matrix. We applied this system to decipher the trans-kingdom interactome between Mycobacterium tuberculosis and host cells and further identified Rv2427c interfering with the phagosome–lysosome fusion. This concept can also be applied to other systems to screen protein–RNA and protein–DNA interactions and delineate signaling landscape in cells.

Malaria, the exterminator of ~1.5 to 2.7 million human lives yearly, is a notorious disease known throughout the world. The eradication of this disease is difficult and a challenge to scientists. Vector elimination and effective chemotherapy for the patients are key tactics to be used in the fight against malaria. However, drug resistance and environmental and social concerns are the main hurdles in this fight against malaria. Overcoming these limitations is the major challenge for the 21st-century malarial researchers. Adapting the principles of nano-biotechnology to both vector control and patient therapy is the only solution to the problem. Several compounds such as lipids, proteins, nucleic acid and metallic nanoparticles (NPs) have been successfully used for the control of this lethal malaria disease. Other useful natural reagents such as microbes and their products, carbohydrates, vitamins, plant extracts and biodegradable polymers, are also used to control this disease. Among these particles, the plant-based particles such as leaf, root, stem, latex, and seed give the best antagonistic response against malaria. In the present review, we describe certain efforts related to the control, prevention and treatment of malaria. We hope that this review will open new doors for malarial research.