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OPTIMIZATION OF THE BIOSORPTION OF Cr3+, Cd2+ AND Pb2+ USING A NEW BIOWASTE: Zea mays SEED CHAFF
(2016)
This study highlights the potential use of yellow Zea mays seed chaff (YZMSC) biomass as a biosorbent for the removal of Cr3+, Cd2+ and Pb2+ ions from aqueous solutions. Fourier transformed Infrared analysis of the biomass suggests that YZMSC biomass is basically composed of cellulose and methyl cellulose. The biosorption capacities, q(max), of YZMSC biomass for Cr3+, Cd2+ and Pb2+ are 14.68, 121.95 and 384.62 mg/g respectively. Biosorption equilibrium was achieved at 20, 30 and 60 min for Cr3+, Cd2+ and Pb2+ respectively. YZMSC biomass was found to have higher biosorption capacity and overall kinetic rate of uptake for Pb2+ than for Cd2+ and Cr3+. However, Cr3+ had better initial kinetic rate of uptake by the biomass than Pb2+ and Cd2+. The Freundlich equilibrium isotherm model was found to describe equilibrium data better than Langmuir model suggesting that biosorption of these metal ions could be on more than one active site on the surface of YZMSC biomass. Kinetic study predicted the pseudo-second kinetic model as being able to better describe kinetic data obtained than either modified pseudo-first order or Bangham kinetic models. Biosorption of Cr3+, Cd2+ and Pb2+ onto YZMSC biomass was endothermic in nature with large positive entropy values. Biosorption of these metal ions onto YZMSC biomass was observed to be feasible and spontaneous above 283 K. Optimization of biomass weight for the removal of these metal ions suggest that 384 kg, 129 kg and 144 kg of YZMSC biomass is required for the removal of 95% of Cr3+, Cd2+ and Pb2+ metal ions respectively from 100 mg/L of metal ions in 10 tonnes of aqueous solutions.
Land-use intensification is a major driver of biodiversity loss(1,2). Alongside reductions in local species diversity, biotic homogenization at larger spatial scales is of great concern for conservation. Biotic homogenization means a decrease in beta-diversity (the compositional dissimilarity between sites). Most studies have investigated losses in local (alpha)-diversity(1,3) and neglected biodiversity loss at larger spatial scales. Studies addressing beta-diversity have focused on single or a few organism groups (for example, ref. 4), and it is thus unknown whether land-use intensification homogenizes communities at different trophic levels, above-and belowground. Here we show that even moderate increases in local land-use intensity (LUI) cause biotic homogenization across microbial, plant and animal groups, both above- and belowground, and that this is largely independent of changes in alpha-diversity. We analysed a unique grassland biodiversity dataset, with abundances of more than 4,000 species belonging to 12 trophic groups. LUI, and, in particular, high mowing intensity, had consistent effects on beta-diversity across groups, causing a homogenization of soil microbial, fungal pathogen, plant and arthropod communities. These effects were nonlinear and the strongest declines in beta-diversity occurred in the transition from extensively managed to intermediate intensity grassland. LUI tended to reduce local alpha-diversity in aboveground groups, whereas the alpha-diversity increased in belowground groups. Correlations between the alpha-diversity of different groups, particularly between plants and their consumers, became weaker at high LUI. This suggests a loss of specialist species and is further evidence for biotic homogenization. The consistently negative effects of LUI on landscape-scale biodiversity underscore the high value of extensively managed grasslands for conserving multitrophic biodiversity and ecosystem service provision. Indeed, biotic homogenization rather than local diversity loss could prove to be the most substantial consequence of land-use intensification.
The human immunodeficiency virus (HIV) has resisted nearly three decades of efforts targeting a cure. Sustained suppression of the virus has remained a challenge, mainly due
to the remarkable evolutionary adaptation that the virus exhibits by the accumulation of drug-resistant mutations in its genome. Current therapeutic strategies aim at achieving and maintaining a low viral burden and typically involve multiple drugs. The choice of optimal combinations of these drugs is crucial, particularly in the background of treatment failure having occurred previously with certain other drugs. An understanding of the dynamics of viral mutant genotypes aids in the assessment of treatment failure with a certain drug
combination, and exploring potential salvage treatment regimens.
Mathematical models of viral dynamics have proved invaluable in understanding the viral life cycle and the impact of antiretroviral drugs. However, such models typically use simplified and coarse-grained mutation schemes, that curbs the extent of their application to drug-specific clinical mutation data, in order to assess potential next-line therapies. Statistical
models of mutation accumulation have served well in dissecting mechanisms of resistance evolution by reconstructing mutation pathways under different drug-environments. While these models perform well in predicting treatment outcomes by statistical learning, they do not incorporate drug effect mechanistically. Additionally, due to an inherent lack of
temporal features in such models, they are less informative on aspects such as predicting mutational abundance at treatment failure. This limits their application in analyzing the
pharmacology of antiretroviral drugs, in particular, time-dependent characteristics of HIV therapy such as pharmacokinetics and pharmacodynamics, and also in understanding the impact of drug efficacy on mutation dynamics.
In this thesis, we develop an integrated model of in vivo viral dynamics incorporating drug-specific mutation schemes learned from clinical data. Our combined modelling
approach enables us to study the dynamics of different mutant genotypes and assess mutational abundance at virological failure. As an application of our model, we estimate in vivo
fitness characteristics of viral mutants under different drug environments. Our approach also extends naturally to multiple-drug therapies. Further, we demonstrate the versatility of our model by showing how it can be modified to incorporate recently elucidated mechanisms of drug action including molecules that target host factors.
Additionally, we address another important aspect in the clinical management of HIV disease, namely drug pharmacokinetics. It is clear that time-dependent changes in in vivo
drug concentration could have an impact on the antiviral effect, and also influence decisions on dosing intervals. We present a framework that provides an integrated understanding
of key characteristics of multiple-dosing regimens including drug accumulation ratios and half-lifes, and then explore the impact of drug pharmacokinetics on viral suppression.
Finally, parameter identifiability in such nonlinear models of viral dynamics is always a concern, and we investigate techniques that alleviate this issue in our setting.
Climate change and land use management practices are major drivers of biodiversity in terrestrial ecosystems. To understand and predict resulting changes in community structures, individual-based and spatially explicit population models are a useful tool but require detailed data sets for each species. More generic approaches are thus needed. Here we present a trait-based functional type approach to model savanna birds. The aim of our model is to explore the response of different bird functional types to modifications in habitat structure. The functional types are characterized by different traits, in particular body mass, which is related to life-history traits (reproduction and mortality) and spatial scales (home range area and dispersal ability), as well as the use of vegetation structures for foraging and nesting, which is related to habitat quality and suitability. We tested the performance of the functional types in artificial landscapes varying in shrub:grass ratio and clumping intensity of shrub patches. We found that an increase in shrub encroachment and a decrease in habitat quality caused by land use mismanagement and climate change endangered all simulated bird functional types. The strength of this effect was related to the preferred habitat. Furthermore, larger-bodied insectivores and omnivores were more prone to extinction due to shrub encroachment compared to small-bodied species. Insectivorous and omnivorous birds were more sensitive to clumping intensity of shrubs whereas herbivorous and carnivorous birds were most affected by a decreasing amount of grass cover. From an applied point of view, our findings emphasize that policies such as woody plant removal and a reduction in livestock stocking rates to prevent shrub encroachment should prioritize the enlargement of existing grassland patches. Overall, our results show that the combination of an individual-based modelling approach with carefully defined functional types can provide a powerful tool for exploring biodiversity responses to environmental changes. Furthermore, the increasing accumulation of worldwide data sets on species’ core and soft traits (surrogates to determine core traits indirectly) on one side and the refinement of conceptual frameworks for animal functional types on the other side will further improve functional type approaches which consider the sensitivities of multiple species to climate change, habitat loss, and fragmentation.
Fruits exhibit a vast array of different 3D shapes, from simple spheres and cylinders to more complex curved forms; however, the mechanism by which growth is oriented and coordinated to generate this diversity of forms is unclear. Here, we compare the growth patterns and orientations for two very different fruit shapes in the Brassicaceae: the heart-shaped Capsella rubella silicle and the near-cylindrical Arabidopsis thaliana silique. We show, through a combination of clonal and morphological analyses, that the different shapes involve different patterns of anisotropic growth during three phases. These experimental data can be accounted for by a tissue level model in which specified growth rates vary in space and time and are oriented by a proximodistal polarity field. The resulting tissue conflicts lead to deformation of the tissue as it grows. The model allows us to identify tissue-specific and temporally specific activities required to obtain the individual shapes. One such activity may be provided by the valve-identity gene FRUITFULL, which we show through comparative mutant analysis to modulate fruit shape during post-fertilisation growth of both species. Simple modulations of the model presented here can also broadly account for the variety of shapes in other Brassicaceae species, thus providing a simplified framework for fruit development and shape diversity.
Heterostyly is a wide-spread floral adaptation to promote outbreeding, yet its genetic basis and evolutionary origin remain poorly understood. In Primula (primroses), heterostyly is controlled by the S-locus supergene that determines the reciprocal arrangement of reproductive organs and incompatibility between the two morphs. However, the identities of the component genes remain unknown. Here, we identify the Primula CYP734A50 gene, encoding a putative brassinosteroid-degrading enzyme, as the G locus that determines the style-length dimorphism. CYP734A50 is only present on the short-styled S-morph haplotype, it is specifically expressed in S-morph styles, and its loss or inactivation leads to long styles. The gene arose by a duplication specific to the Primulaceae lineage and shows an accelerated rate of molecular evolution. Thus, our results provide a mechanistic explanation for the Primula style-length dimorphism and begin to shed light on the evolution of the S-locus as a prime model for a complex plant supergene.