A comparative study on the production of ethanol from lignocellulosic biomass by chemical and biological method

Ethanol derived from non-edible biomass is renewable and a clean source of energy. It is independent of the food industry and it is economically feasible. The first generation biofuel or bioethanol is still not a very convenient source of energy as it prominently depends on the availability of grains. The main objective of this work is to develop an industrious efficient process to produce ethanol from lignocellulosic biomasses like wood and leaf in a lab scale. Two processes were compared. The first process involved an alkaline pre-treatment of the powdered biomass followed by dilute acid hydrolysis. The second process involved an alkaline treatment followed by direct hydrolysis of the biomass by use of a fungal species obtained from rotting wood. Following hydrolysis, fermentation was performed using _Saccharomyces cerevisiae_ and ethanol produced was measured. The process methodologies performed here are liable to be scaled up easily. The final study determines factors such as temperature, strength of the reagents and retention time to maximize ethanol production

Parikh Image of Pushdown Automata

We compare pushdown automata (PDAs for short) against other representations. First, we show that there is a family of PDAs over a unary alphabet with $n$ states and $p \geq 2n + 4$ stack symbols that accepts one single long word for which every equivalent context-free grammar needs $\Omega(n^2(p-2n-4))$ variables. This family shows that the classical algorithm for converting a PDA to an equivalent context-free grammar is optimal even when the alphabet is unary. Moreover, we observe that language equivalence and Parikh equivalence, which ignores the ordering between symbols, coincide for this family. We conclude that, when assuming this weaker equivalence, the conversion algorithm is also optimal. Second, Parikh's theorem motivates the comparison of PDAs against finite state automata. In particular, the same family of unary PDAs gives a lower bound on the number of states of every Parikh-equivalent finite state automaton. Finally, we look into the case of unary deterministic PDAs. We show a new construction converting a unary deterministic PDA into an equivalent context-free grammar that achieves best known bounds.Comment: 17 pages, 2 figure

A COMPREHENSIVE REVIEW ON ADULTERATION OF RAW MATERIALS USED IN ASU DRUG MANUFACTURING

Ayurveda is a system of Indian traditional form of alternative medicine. In 20th and 21th century due to side effects of synthetic drugs, there is an increasing interesting ASU medicine. At present the adulteration of the herbal drugs is the burning problem in ASU herbal industry and it has caused a major problem in the research on commercial natural products. The deforestation and extinction of many species and incorrect identification of many plants has resulted in adulteration and substitution of raw drugs. The future development of analysis of herbs is largely depended upon reliable methodologies for correct identification, standardization and quality assurance of Ayurvedic drugs. In India normally the contamination/adulteration in food/crude drugs is done either for financial gain or due to carelessness and lack in proper hygienic condition of processing, storing, transportation and marketing. Medicinal plants constitute an effective source of traditional and modern medicine. Adulteration is considered as an intentional addition of foreign substances to increase the weight of the product or to decrease its cost. It may be due to- Confusion in vernacular names, Lack of knowledge about authentic plants, Non availability, Similarity in morphology, activity, aroma, Careless collection and other unknown reasons. This article throws a light on adulteration, types, common market adulterants in ASU medicines and prescribed Prevention methods

An Innovative Strategy for Dual Inhibitor Design and Its Application in Dual Inhibition of Human Thymidylate Synthase and Dihydrofolate Reductase Enzymes

Due to the diligence of inherent redundancy and robustness in many biological networks and pathways, multitarget inhibitors present a new prospect in the pharmaceutical industry for treatment of complex diseases. Nevertheless, to design multitarget inhibitors is concurrently a great challenge for medicinal chemists. We have developed a novel computational approach by integrating the affinity predictions from structure-based virtual screening with dual ligand-based pharmacophore to discover potential dual inhibitors of human Thymidylate synthase (hTS) and human dihydrofolate reductase (hDHFR). These are the key enzymes in folate metabolic pathway that is necessary for the biosynthesis of RNA,DNA, and protein. Their inhibition has found clinical utility as antitumor, antimicrobial, and antiprotozoal agents. A druglike database was utilized to perform dual-target docking studies. Hits identified through docking experiments were mapped over a dual pharmacophore which was developed from experimentally known dual inhibitors of hTS and hDHFR. Pharmacophore mapping procedure helped us in eliminating the compounds which do not possess basic chemical features necessary for dual inhibition. Finally, three structurally diverse hit compounds that showed key interactions at both activesites, mapped well upon the dual pharmacophore, and exhibited lowest binding energies were regarded as possible dual inhibitors of hTS and hDHFR. Furthermore, optimization studies were performed for final dual hit compound and eight optimized dual hits demonstrating excellent binding features at target systems were also regarded as possible dual inhibitors of hTS and hDHFR. In general, the strategy used in the current study could be a promising computational approach and may be generally applicable to other dual target drug designs