Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae) is one of the major insect pests of stored grains. Due to export legislation and zero-tolerance for live insect in trade commodities, extensive use of synthetic insecticides is in practice in order to eliminate pest infestations from the lots. Currently, the one and only acceptable chemical to be used in stored grain is phosphine but due to its excessive usage the stored grain pests are becoming resistant against it. Hence discovery of alternative compounds is much needed. In this study we have compared insecticidal efficacy of different plant materials from six commonly grown plants of Pakistan, viz. Allium sativum (Alliaceae), Zingiber officinale (Zingiberaceae), Cymbopogon citratus (Poaceae), Eucalyptus globulus (Myrtaceae), Nicotiana tabacum (Solanaceae), and Azadirachta indica (Meliaceae) against T. castaneum infesting stored wheat, rice, corn and gram pulse. Various plant parts were dried, powdered, and used as admixtures to the stored commodities in the experiments. The results have suggested that A. sativum (garlic) and Z. officinale (ginger) were more effective resulting into 15 times higher adult mortality and 4 to 5 times reduction in grain weight losses when mixed with rice grains. Similarly, A. indica when admixture with wheat checked the population growth in the resources resulting into 3.5 times less adult production compared to controls. A subsequent experiment was conducted to study the dose response of neem seed powder against the beetle pest infesting milled products. Surprisingly, better control was observed either at lowest (1% w/w) or the highest doses (5% w/w). This finding is of great interest to understand the underlying phenomenon which we assume is the ability of T. castaneum to feed selectively in flour mediums, however, further research on this aspect is required to be investigated. The results of this study support the use of botanicals for stored product pest management.

Background: As the number of elderly persons increases, neurodegenerative diseases are becoming ubiquitous. There is currently a great need for knowledge concerning management of old-age neurodegenerative diseases; the most important of which are: Alzheimer’s disease, Parkinson’s disease, Amyotrophic Lateral Sclerosis, and Huntington’s disease. Objective: To summarize the potential of computationally predicted molecules and targets against neurodegenerative diseases. Method: Review of literature published since 1997 against neurodegenerative diseases, utilizing as keywords: in silico, Alzheimer’s disease, Parkinson’s disease, Amyotrophic Lateral Sclerosis ALS, and Huntington’s disease. Results and Conclusion: Due to the costs associated with experimentation and current ethical law, performing experiments directly on living organisms has become much more difficult. In this scenario, in silico techniques have been successful and have become powerful tools in the search to cure disease. Researchers use the Computer Aided Drug Design pipeline which: 1) generates 3-dimensional structures of target proteins through homology modeling 2) achieves stabilization through molecular dynamics simulation, and 3) exploits molecular docking through large compound libraries. Next generation sequencing is continually producing enormous amounts of raw sequence data while neuroimaging is producing a multitude of raw image data. To solve such pressing problems, these new tools and algorithms are required. This review elaborates precise in silico tools and techniques for drug targets, active molecules, and molecular docking studies, together with future prospects and challenges concerning possible breakthroughs in Alzheimer’s, Parkinson’s, Amyotrophic Lateral Sclerosis, and Huntington’s disease.