Use of indigenous knowledge in the management of field and storage pests around Lake Victoria basin in Tanzania

Agriculture in Lake Victoria basin (LVB) in Tanzania is predominantly subsistence and is characterised by perennial food deficits, cyclic famines and poverty prompted largely by unreliable rainfall patterns, declining soil fertility and food grains pests and diseases. The pest problem is more pronounced as farmers are yet to fully integrate synthetic pesticides into their insect pest management systems due to subsistence nature of production and high poverty levels that make them rely on indigenous knowledge (IK) systems to meet their needs. The survey was conducted to document farmers’ IK on management of key field and storage insect pests in Magu and Misungwi districts in the LVB, Tanzania. Major crops grown were maize, rice, sorghum, finger millet, bean, groundnut, cowpea, green gram, brassicas, chicken pea, cassava, sweet potato, cotton and vegetables. Crops were mainly infested by Busseola fusca (Lepidoptera: Noctuidae), Spodoptera spp (Lepidoptera: Noctuidae), Agrotis spp (Lepidoptera: Noctuidae), Maruca vitrata (Lepidoptera: Crambidae), Rhopalosiphum maidis (Homoptera: Aphididae), Aphis fabae (Hemiptera: Aphididae), and grasshoppers in field and Stophilus spp (Coleoptera: Curculionidae), Prostephanus truncates (Coleoptera: Bostrichidae), Tribolium spp (Coleoptera: Tenebrionidae), Bruchus rufimanus (Coleoptera; Bruchidae), Rhyzopertha dominica (Coleoptera: Bostrichidae) and rodents on storage. IK based control methods used by farmers ranged from animal by-products (cow’s urine and dung), plant parts (Azadirachta indica (Meliaceae),Tephrosia vogelii (Fabaceae), Tamarindus indica (Fabaceae), Aloe spp (Asphodelaceae), red pepper, Capsicum spp (Solanaceae), Nicotiana tabasum (Solanaceae) to ash (general and specific) in the field. They also used neem, Chenopodium opulifolium (Chenopodiaceae), Ocimum suave (Labiatae), Senna siamea (Fabaceae or Caesalpinioideae), tobacco and Eucalyptus spp (Myrtaceae) and plant by-products (rice husks, ash from rice husks and red maize cobs and general ash) to control storage pests. Most of these products were used together with one or two others in different formulation mixtures. However, the formulations had variable amount taken during preparation, crop/ crop product treated, preparation times, modes and rates of application. Research is needed to unveil the amount for mixing, appropriate treatment, and application rate to ensure optimum concentration for specific pest. To ensure quality and safety, biosafety and quality studies are required for quality assessment of resulting product for human health. For understanding of active compounds in the formulations, chemical composition analysis of properly prepared solutions is required. Key words: Field and storage pests, indigenous knowledge, Tanzania, botanical formulation, Lake Victoria basin

Oral acute toxicity study of selected botanical pesticide plants used by subsistence farmers around the Lake Victoria Basin

A survey carried out around the Lake Victoria region showed evidence that people around this region use plant extracts, parts and powders to protect stored food commodities from insect pests. The widely used plants were identified and selected for biosafety assessments namely: Ocimum gratissimum, Tithonia diversifolia, Eucalyptus saligna, Eucalyptus globulus and Cupressus lusitanica. Wistar mice were acclimatized and divided into groups of six. Each mice group was administered with one extract at different concentrations. The extracts were administered orally and the animals were observed for 24 h. A control group was kept which received only the carrier substance orally. The LD50 values were determined by the use of the graphical method and regression analysis. Oral acute toxicity studies established the LD50 values for essential oils of O. gratissimum, E. saligna and C. lusitanica as 4.570, 2.290, and 3.311 mg/kg, respectively. For ethanol extracts, LD50 values were 12.882, 12.302, 14.996 and 11.481 mg/kg for O. gratissimum, E. globulus, C. lusitanica and T. diversifolia, respectively. For the aqueous extracts, the LD50 of T. diversifolia was found to be 12.302 mg/kg. For E. globulus and C. lusitanica, their aqueous LD50s were beyond 15.000 mg/kg. The oral acute toxicity tests showed weak toxicities for all the plant extracts investigated in the study. The low toxicity levels exhibited by these extracts may be the reason why these plant products have been used by local communities for long without adverse effects. Chronic studies should be carried out to assess whether these extracts have serious effects on experimental animals exposed to them at small doses for a long period of time.Key words: Oral acute toxicity, biopesticide, plant extracts, Lake Victoria Basin

Discovering patterns in drug-protein interactions based on their fingerprints

<p>Abstract</p> <p>Background</p> <p>The discovering of interesting patterns in drug-protein interaction data at molecular level can reveal hidden relationship among drugs and proteins and can therefore be of paramount importance for such application as drug design. To discover such patterns, we propose here a computational approach to analyze the molecular data of drugs and proteins that are known to have interactions with each other. Specifically, we propose to use a data mining technique called <it>Drug-Protein Interaction Analysis </it>(<it>D-PIA</it>) to determine if there are any commonalities in the fingerprints of the substructures of interacting drug and protein molecules and if so, whether or not any patterns can be generalized from them.</p> <p>Method</p> <p>Given a database of drug-protein interactions, <it>D-PIA </it>performs its tasks in several steps. First, for each drug in the database, the fingerprints of its molecular substructures are first obtained. Second, for each protein in the database, the fingerprints of its protein domains are obtained. Third, based on known interactions between drugs and proteins, an interdependency measure between the fingerprint of each drug substructure and protein domain is then computed. Fourth, based on the interdependency measure, drug substructures and protein domains that are significantly interdependent are identified. Fifth, the existence of interaction relationship between a previously unknown drug-protein pairs is then predicted based on their constituent substructures that are significantly interdependent.</p> <p>Results</p> <p>To evaluate the effectiveness of <it>D-PIA</it>, we have tested it with real drug-protein interaction data. <it>D-PIA </it>has been tested with real drug-protein interaction data including enzymes, ion channels, and protein-coupled receptors. Experimental results show that there are indeed patterns that one can discover in the interdependency relationship between drug substructures and protein domains of interacting drugs and proteins. Based on these relationships, a testing set of drug-protein data are used to see if <it>D-PIA </it>can correctly predict the existence of interaction between drug-protein pairs. The results show that the prediction accuracy can be very high. An AUC score of a ROC plot could reach as high as 75% which shows the effectiveness of this classifier.</p> <p>Conclusions</p> <p><it>D-PIA </it>has the advantage that it is able to perform its tasks effectively based on the fingerprints of drug and protein molecules without requiring any 3D information about their structures and <it>D-PIA </it>is therefore very fast to compute. <it>D-PIA </it>has been tested with real drug-protein interaction data and experimental results show that it can be very useful for predicting previously unknown drug-protein as well as protein-ligand interactions. It can also be used to tackle problems such as ligand specificity which is related directly and indirectly to drug design and discovery.</p

Comparative structural evolution under pressure of powder and single crystals of the layered antiferromagnet FePS3

FePS3 is a layered magnetic van der Waals compound that undergoes a Mott insulator-metal transition under applied pressure. The transition has an associated change in the crystal symmetry and magnetic structure. Understanding the underlying physics of these transitions requires a detailed understanding of the crystal structure as a function of pressure. Two conflicting models have previously been proposed for the evolution of the structure with pressure. To settle the disagreement, we present a study of the pressure-dependent crystal structures using both single-crystal and powder x-ray diffraction measurements. We show unambiguously that the highest-pressure transition involves a collapse of the interplanar spacing, along with an increase in symmetry from a monoclinic to a trigonal space group, to the exclusion of other models. Our collected results are crucial for understanding high-pressure behavior in these materials and demonstrate a clear and complete methodology for exploring complex two-dimensional material structures under pressure

Virtual screening for inhibitors of the human TSLP:TSLPR interaction

The pro-inflammatory cytokine thymic stromal lymphopoietin (TSLP) plays a pivotal role in the pathophysiology of various allergy disorders that are mediated by type 2 helper T cell (Th2) responses, such as asthma and atopic dermatitis. TSLP forms a ternary complex with the TSLP receptor (TSLPR) and the interleukin-7-receptor subunit alpha (IL-7Ra), thereby activating a signaling cascade that culminates in the release of pro-inflammatory mediators. In this study, we conducted an in silico characterization of the TSLP: TSLPR complex to investigate the drugability of this complex. Two commercially available fragment libraries were screened computationally for possible inhibitors and a selection of fragments was subsequently tested in vitro. The screening setup consisted of two orthogonal assays measuring TSLP binding to TSLPR: a BLI-based assay and a biochemical assay based on a TSLP: alkaline phosphatase fusion protein. Four fragments pertaining to diverse chemical classes were identified to reduce TSLP: TSLPR complex formation to less than 75% in millimolar concentrations. We have used unbiased molecular dynamics simulations to develop a Markov state model that characterized the binding pathway of the most interesting compound. This work provides a proof-ofprinciple for use of fragments in the inhibition of TSLP: TSLPR complexation

Transfer Functions for Protein Signal Transduction: Application to a Model of Striatal Neural Plasticity

We present a novel formulation for biochemical reaction networks in the context of signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of 'source' species, which receive input signals. Signals are transmitted to all other species in the system (the 'target' species) with a specific delay and transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and recalled to build discrete dynamical models. By separating reaction time and concentration we can greatly simplify the model, circumventing typical problems of complex dynamical systems. The transfer function transformation can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant insight, while remaining an executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modules that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. We also found that overall interconnectedness depends on the magnitude of input, with high connectivity at low input and less connectivity at moderate to high input. This general result, which directly follows from the properties of individual transfer functions, contradicts notions of ubiquitous complexity by showing input-dependent signal transmission inactivation.Comment: 13 pages, 5 tables, 15 figure

Fabrication and operation of a two-dimensional ion-trap lattice on a high-voltage microchip

Microfabricated ion traps are a major advancement towards scalable quantum computing with trapped ions. The development of more versatile ion-trap designs, in which tailored arrays of ions are positioned in two dimensions above a microfabricated surface, will lead to applications in fields as varied as quantum simulation, metrology and atom–ion interactions. Current surface ion traps often have low trap depths and high heating rates, because of the size of the voltages that can be applied to them, limiting the fidelity of quantum gates. Here we report on a fabrication process that allows for the application of very high voltages to microfabricated devices in general and use this advance to fabricate a two-dimensional ion-trap lattice on a microchip. Our microfabricated architecture allows for reliable trapping of two-dimensional ion lattices, long ion lifetimes, rudimentary shuttling between lattice sites and the ability to deterministically introduce defects into the ion lattice

Modulation of the virus-receptor interaction by mutations in the V5 loop of feline immunodeficiency virus (FIV) following in vivo escape from neutralising antibody

&lt;b&gt;BACKGROUND:&lt;/b&gt; In the acute phase of infection with feline immunodeficiency virus (FIV), the virus targets activated CD4+ T cells by utilising CD134 (OX40) as a primary attachment receptor and CXCR4 as a co-receptor. The nature of the virus-receptor interaction varies between isolates; strains such as GL8 and CPGammer recognise a "complex" determinant on CD134 formed by cysteine-rich domains (CRDs) 1 and 2 of the molecule while strains such as PPR and B2542 require a more "simple" determinant comprising CRD1 only for infection. These differences in receptor recognition manifest as variations in sensitivity to receptor antagonists. In this study, we ask whether the nature of the virus-receptor interaction evolves in vivo.&lt;p&gt;&lt;/p&gt; &lt;b&gt;RESULTS:&lt;/b&gt; Following infection with a homogeneous viral population derived from a pathogenic molecular clone, a quasispecies emerged comprising variants with distinct sensitivities to neutralising antibody and displaying evidence of conversion from a "complex" to a "simple" interaction with CD134. Escape from neutralising antibody was mediated primarily by length and sequence polymorphisms in the V5 region of Env, and these alterations in V5 modulated the virus-receptor interaction as indicated by altered sensitivities to antagonism by both anti-CD134 antibody and soluble CD134.&lt;p&gt;&lt;/p&gt; &lt;b&gt;CONCLUSIONS:&lt;/b&gt; The FIV-receptor interaction evolves under the selective pressure of the host humoral immune response, and the V5 loop contributes to the virus-receptor interaction. Our data are consistent with a model whereby viruses with distinct biological properties are present in early versus late infection and with a shift from a "complex" to a "simple" interaction with CD134 with time post-infection.&lt;p&gt;&lt;/p&gt

Grassmannian flows and applications to nonlinear partial differential equations

We show how solutions to a large class of partial differential equations with nonlocal Riccati-type nonlinearities can be generated from the corresponding linearized equations, from arbitrary initial data. It is well known that evolutionary matrix Riccati equations can be generated by projecting linear evolutionary flows on a Stiefel manifold onto a coordinate chart of the underlying Grassmann manifold. Our method relies on extending this idea to the infinite dimensional case. The key is an integral equation analogous to the Marchenko equation in integrable systems, that represents the coodinate chart map. We show explicitly how to generate such solutions to scalar partial differential equations of arbitrary order with nonlocal quadratic nonlinearities using our approach. We provide numerical simulations that demonstrate the generation of solutions to Fisher--Kolmogorov--Petrovskii--Piskunov equations with nonlocal nonlinearities. We also indicate how the method might extend to more general classes of nonlinear partial differential systems.Comment: 26 pages, 2 figure